Mobile phones
and road safety
Collective Expert Report
2011
This document presents the synthesis and recommendations of the group of experts brought
together by the French National Institute for Health and Medical Research (Inserm) and the
French Institute for Transport, Urban Planning and Network Sciences and Technologies
(IFSTTAR, formerly INRETS) within the framework of the collective expertise procedure
(see Appendix), in response to a request by the French Ministry for Ecology, Energy,
Sustainable Development and the Sea's Delegation on Safety and Road Traffic concerning the
risks linked to mobile phone use while driving.
This work is based on the scientific data available during the first half of 2010. The
information contained in almost 400 documents provides the basis for this expert report.
The Inserm Collective Expertise Center, linked to the Multi-Organism Thematic Institute
(ITMO) for Public Health, and IFSTTAR co-ordinated this expert report.
Collective Expert Report
-2-
13/12/2011
Group of experts and authors
Corinne BRUSQUE, Ergonomics and Cognitive Science Laboratory for Transport (Lescot),
IFSTTAR, Bron
Marie-Pierre BRUYAS, Ergonomics and Cognitive Science Laboratory for Transport (Lescot),
IFSTTAR, Bron
Colette FABRIGOULE, Molecular and functional imaging, UMR (Medical Research Unit) 5231,
CNRS (French National Center for Scientific Research), Victor Segalen University,
Bordeaux 2
Fabrice HAMELIN, Economics and Sociology Department for Transport (DEST), IFSTTAR,
Noisy le Grand
Martine HOURS, Joint epidemiological research and transport, work and environment
surveillance unit (UMRESTTE), UMR 9405, IFSTTAR-University of Lyons 1, Bron
Emmanuel LAGARDE, Injury Prevention and Control, Inserm U 897, Bordeaux Segalen
University
Jean-Louis MARTIN, Joint epidemiological research and transport, work and environment
surveillance unit (UMRESTTE), UMR 9405, IFSTTAR-University of Lyons 1, Bron
Dominique MIGNOT, Economist, Scientific Department, IFSTTAR, Bron
Pierre VAN ELSLANDE, Accident Mechanisms Laboratory (MA), IFSTTAR, Salon de Provence
Contributors
René AMALBERTI, Research and innovation in inland transport program (PREDIT) and the
French National Authority for Health, Saint-Denis-la-Plaine
François BELLAVANCE, Quantitative Management Methods Teaching Service, HEC Montreal,
Quebec
Jean-Pierre CAUZARD, Driving Psychology Laboratory (LPC), IFSTTAR, Satory
Jean-Marie DANJOU, French Mobile Operators Associations (AFOM), Paris
Thierry FASSENOT, Department for professional risk prevention, French National Sickness
Insurance Fund for Employed Workers (CNAMTS), Paris
Claude GOT, Paris-Ouest Faculty of Medicine, René Descartes University, Paris
Anne GUILLAUME, Accidentology and Biomechanics Laboratory (Lab), GIE PSA Peugeot
Citroën and Renault, Nanterre
Marc HEDDEBAUT, Electronics, Waves and Signals Laboratory for Transport (LEOST),
IFSTTAR, Villeneuve-d’Ascq
Bernard LAUMON, Joint epidemiological research and transport, work and environment
surveillance unit (UMRESTTE), UMR 9405, IFSTTAR-University of Lyons 1, Bron
Michael REGAN, Ergonomics and Cognitive Sciences Laboratory for Transport (LESCOT),
IFSTTAR, Bron, and University of Melbourne, Australia
Alan STEVENS, Transport Research Laboratory (TRL), Berkshire, Great Britain
Collective Expert Report
-3-
13/12/2011
Scientific, editorial, bibliographical and logistical co-ordination
Fabienne BONNIN, Expertise Officer, Inserm Collective Expertise Center, Xavier-Bichat
Faculty of Medicine, Paris
Catherine CHENU, Scientific Attaché, Inserm Collective Expertise Center, Xavier-Bichat
Faculty of Medicine, Paris
Jeanne ÉTIEMBLE, Director (until August 2010), Inserm Collective Expertise Center, XavierBichat Faculty of Medicine, Paris
Cécile GOMIS, Secretary, Inserm Collective Expertise Center, Xavier-Bichat Faculty of
Medicine, Paris
Bernard LAUMON, Director of Research, Joint epidemiological research and transport, work
and environment surveillance unit (UMRESTTE), UMR 9405, IFSTTAR-University of Lyons
1, Bron
Marie-Christine LECOMTE, Director, Inserm Collective Expertise Center, Xavier-Bichat
Faculty of Medicine, Paris
Anne-Laure PELLIER, Scientific Attaché, Inserm Collective Expertise Center, Xavier-Bichat
Faculty of Medicine, Paris
Chantal RONDET-GRELLIER, Research Assistant, Inserm Collective Expertise Center, XavierBichat Faculty of Medicine, Paris
Iconography
Jean-Pierre LAIGNEAU, Inserm
Collective Expert Report
-4-
13/12/2011
Contents
Foreword .................................................................................................................................... 6
Analysis...................................................................................................................................... 8
Human factors and causality of road accidents.......................................................................... 9
Psychocognitive processes involved in driving a road vehicle ................................................ 23
The impact of mobile phone use on the driving activity.......................................................... 32
Prevalence of mobile phone use at the wheel and accidents.................................................... 48
Epidemiological approach of the risk of an accident linked to telephoning while driving...... 67
Drivers’ perception of the risk linked to phoning while driving.............................................. 87
From regulations to debate: government responses to mobile phone use while driving ......... 97
Socioeconomic impact of the ban on telephoning while driving ........................................... 111
Summary ................................................................................................................................ 125
Recommendations .................................................................................................................. 143
Communications..................................................................................................................... 153
Distraction, telephoning while driving, driving routines and cognition ................................ 155
Travel speed and other road accident factors ......................................................................... 159
Telephoning while driving: what are the biases? ................................................................... 165
Prevention of the road risk in the workplace: what can be proposed?................................... 169
Safety implications of mobile phone usage by drivers: Legal Situation, Research Studies and
Outlook................................................................................................................................... 179
Driver Distraction: Definition, Mechanisms, Effects and Mitigation.................................... 187
Point of view of the Laboratory of accidentology and biomechanics (LAB) ........................ 203
Appendix ................................................................................................................................ 207
Collective Expert Report
-5-
13/12/2011
Foreword
Since the 1970s, road accidents have been the target of a road safety policy in France aiming
to reduce the number of road deaths. The first measures pertained to the limiting of blood
alcohol content, obligatory seat belt wearing and limiting speed. These were followed by a
continuous decline in the number of road deaths, which decreased from 16,000 per year in
1972 to 4,000 in 2007. This decrease has also been observed in other European countries. At
the same time as a public initiative to crack down on behaviors which were considered highrisk, improvements in the road environment and vehicle equipment have contributed to the
reduction of road traumas.
Knowledge produced by scientific research now shows that driving a vehicle should be
considered as a complex task, the performance of which is subject to numerous individual
and environmental factors.
Among the factors likely to affect driving abilities and cause accidents, distractions at the
wheel have been the subject of growing attention for approximately 20 years, in particular
distractions linked to use of telecommunications systems. In fact, the exponential and rapid
development of mobile phones used by everybody and in all everyday situations, as well as
the construction of vehicles that are increasingly equipped with telematic systems, justify
this concern.
Use of hand-held mobile phones while driving has been banned in France since 2003 and has
been the subject of regular awareness-raising media campaigns by the government.
However, the impact of these measures and the risk associated with the use of 'hands-free'
mobile phones and their new uses (e.g. SMS text messages, internet consultation), as well as
that of navigation systems, has received little in the way of evaluation.
The French Ministry for Ecology, Energy, Sustainable Development and the Sea's Delegation
on Safety and Road Traffic has entrusted the French National Institute for Health and
Medical Research (Inserm), in partnership with the French Institute for Transport, Urban
Planning and Network Sciences and Technologies (IFSTTAR), with carrying out a Collective
Expert Report on the impact of mobile phone use on road users' safety with reference to
other sources of distractions for the driver. The objective is to assess the scientific literature
on the impact of the use of cell phones (hand-held and 'hands-free') as well as other
information and communications systems by road vehicle drivers on the risk of accidents.
In order to respond to this request, Inserm and IFSTTAR have brought together a
multidisciplinary group of nine experts who are specialists in various scientific disciplines
applying to the study of road safety: epidemiology, cognitive science, psychology,
ergonomics, economics and political science.
The group of experts has focused its deliberations on the following questions:
•
What is our current understanding of the cognitive processes involved in the
driving of road vehicles (e.g. attentional processes, decision-making processes,
basic vigilance)?
•
Do we know how these different processes are involved in the risk of accidents?
•
What knowledge do we possess concerning the impact of use of electronic
communication instruments (mobile phone, navigation systems) on the abilities
and performance of driving a vehicle?
Collective Expert Report
-6-
13/12/2011
•
What is the data on the perception of the risk of accidents linked to use of mobile
phones and other communication technologies at the wheel among drivers
(awareness, attitudes, behaviors)?
•
What are the types of studies enabling evaluation of the risk of accidents linked to
use of mobile phones and other communication technologies at the wheel?
•
What data is available in France and abroad on the risk of road accidents (e.g.
frequency, severity) linked to use of mobile phones and other communication
technologies at the wheel?
•
Is the risk of accidents linked to use of mobile phones while driving associated
with individual factors (e.g. gender, age, distance traveled)?
•
What are the forms of public action concerning use of cell phones at the wheel in
France, in different European countries and outside Europe? Do we know what
their impact has been?
•
Is it possible to estimate the cost to society of road accidents attributed to use of
mobile phones at the wheel and the cost-benefit ratio of measures aiming to
regulate this use?
In order to complete the assessment of knowledge resulting from scientific literature and to
inform its deliberations, the group of experts has heard from 11 key figures, researchers,
representatives of automobile manufacturers, telephony operators and the French National
Sickness Insurance Fund, which have contributed a point of view or an approach to the
issue. Some of these contributors have provided texts which are presented in the
"Communications" section of this report.
Collective Expert Report
-7-
13/12/2011
Analysis
Collective Expert Report
-8-
13/12/2011
1
Human factors and causality of road accidents
The issue of human factors in research into the causality of accidents is a subject that is both
complicated and recurrent in the field of road safety. One of the difficulties is that accidents
most often result from complex and multifactorial phenomena which are difficult to
disentangle. Another difficulty is that studies are based on concepts which do not always
have homogenous definitions. Among the various human factors studied in the literature,
this chapter aims to examine ideas of vigilance, attention and distraction, by taking account
of the processes they correspond to and assessing their role in accidents. Mobile phone use
while driving is subsequently discussed from the point of view of the involvement of these
processes and of the dysfunctions to which they may be subject.
Human factors and accidents
The notion of human factors refers to the ensemble of the variables linked to an individual
and likely to have an impact on driving behavior and on the occurrence of an accident (Elvik
and Vaa, 2004). The vagueness of such a notion thus leads to the inclusion within such an
ensemble of: demographic variables such as age or sex; physiological variables such as
fatigue, health problems, intoxication by alcohol or other drugs; psychological variables such
as inattention or distraction; attitudinal variables such as risk taking; and still other variables
such as experience and practice. Such an imprecise notion leads to incorporate also the
resultant of those different variables that are observable behaviors and notably human errors
(of perception, anticipation, evaluation, action, etc.) that are noted at the end of the process.
So it can lead to confuse the causes and their effects.
Causal approaches aiming to show the part human factors play in the occurrence of an
accident were mainly developed up until the end of the 1990s. These tend to demonstrate the
overriding character of these human factors as regard as factors linked to infrastructure and
vehicles. The weakness of most of this research is that it is not based on rigorously
established models of analysis, whether it deals with accident models or human performance
models. This absence of a use of models translates into data which is set out without much
relationship between one set of data and another. For example, Elgarov (1995) suggests that
errors made by drivers were at the origin of 76% of the 879 accidents studied, these errors
referring to parameters which were of a quite different nature from each other: speed
(19.3%), dangerous overtaking (19.2%) and driving while under the influence of alcohol
(13.4%).
It is in this sense that the notion of human factors is considered elusive, even misleading, by
certain authors specializing in these issues (Hollnagell and Amalberti, 2001). In fact, the
contribution of such factors is far from being so clearly isolated in accident mechanisms,
whether in relation to automobile driving or other activities. This is explained by the fact that
in all complex systems, and in particular traffic systems, the origin of problems is very much
more located in interactions between elements (figure 1.1) that make up said system than in
the exclusive characteristics of one or another of these components. (Van Elslande, 2003). It is
helpful to understand that one single factor is not enough to cause an accident. Most often, it
is a combination of contributing factors that constitute a cluster of causes from which an
Collective Expert Report
-9-
13/12/2011
accident arises. This is confirmed by significant research in ergonomic psychology, as well as
in accidentology: in the majority of accidents, various levels of human, technical and
contextual factors interact with one another to cause a dysfunction, where in isolation they
would not have led to any difficulty. It is therefore necessary to keep in mind the relative
character of the involvement of any given factor, in relation to the context in which this
factor is active. It is also necessary to differentiate human error from the factors (human and
contextual) that have produced it, due to the risk of mixing causes and their effects. Lastly,
the elements that determine the ensemble of our behaviors must not be forgotten: road
characteristics, vehicle characteristics and, even before these, the values present in society
regarding, for example, speed, competition and profitability.
The generalization of this "system" approach as an accident analysis model has brought
about a new perspective on accident phenomena: by no longer seeking to determine which is
more or less at fault, but to identify the most recurrent dysfunctions in the interactions which
establish themselves between the various components making up the system; and by
retaining the objective of reducing these problems of interaction by acting on the ensemble of
these components. It may be more workable to modify the environment rather than
sanctioning users, for example in order to reduce the speed of traffic in certain situations; it is
sometimes counterproductive to give too much information to drivers, as it risks
overburdening them.
Figure 1.1: Interactions between user-vehicle-environment components of the traffic system
(according to Van Elslande, 2003)
Furthermore, it is important to consider, on balance, the positive character of the "human
factor": it constitutes a fundamental, irreplaceable element on which the traffic system
strongly relies in order to function, despite the difficulties it brings with it. An essential
characteristic of human operators rests on their capacity to adapt to complex, variable,
changing and uncertain environments. This ability to adapt notably relies on the aptitude to
make use of cognitive heuristics when an algorithmic function 1 is no longer possible. By
definition, heuristics are rapid, economic and largely efficient processes, but they do not
necessarily lead to a good result. They thus contain a margin of error which is not always
easy to manage. These are the same processes that enable humans to adapt to difficulties in
their environment and which sometimes lead them to make errors. This is the underlying
concept behind the definition of the human being as "agent of fallible reliability" defended by
ergonomic psychology (Leplat, 1999). By its own design, the traffic system leads humans to
move through a complex, variable, changing and uncertain environment, in which the risk of
error is an inevitable element. This system also makes use of the human being's ability to
adapt and, to a certain extent, this ability to commit errors and to more often than not correct
1
In the sense of an ordered sequence of stages of reasoning which enable the individual to resolve a problem.
Collective Expert Report
- 10 -
13/12/2011
the most significant errors. It is this ability that enables humans to drive and, thus, the
driving system to function.
In summary, in the same way as the notion of "behavior", the "human factor" can thus easily
become an all-embracing concept on which everyone has the tendency to project their
ideological and moral prejudices (Whittingham, 2004; Gusfield, 2009), to arrive at the
journalistic mantra that human factors are responsible for 95% of accidents. This conceptual
flow thus falls into the trap outlined above and leads to tautological results that ultimately
show that the user of a system is the major cause of problems, without considering the issue
of the necessary adaptation of socio-technical systems to the users for whom they are
destined. It is effectively possible to confirm that in the case of nearly all accidents, the
deterioration in driving situations will pass through a human inability to control the
situation: in fact, it could not be any other way, as it is the human being who intervenes at
the end of the process. However, we could also bring to mind the fact that it is also humans
that design and maintain the vehicles and infrastructures, define the laws and construct the
social values. Beyond some rare unpredictable phenomena, in the field of driving it is easy to
attribute everything to human beings. In this respect, a scientific approach becomes
necessary to make progress in the understanding of the phenomena involved. Underlying
this approach will be the principle that, in order to make progress in a situation, the objective
should not be to lay the blame on one element or another of a system, but to aim for an
understanding of the ensemble of the origin of the difficulties and to seek ways in which to
overcome these.
Among the "human factors" those which are most often emphasized are typically: speed,
alcohol and drowsiness. Each of these variables has been the subject of abundant literature
which has largely proven their harmful effect on the activity of driving. Linked to the
problem of mobile phone use at the wheel, the following text will highlight the issues of
vigilance and attention, by describing the processes that these concepts cover and the
dysfunctions that these processes can lead to in subjects in a driving situation.
Vigilance and attention
In common usage, the notions of vigilance and attention are often considered equivalent.
Standard dictionaries do not always make a clear distinction between these two terms,
linking them and sometimes presenting them as synonyms. This is also often the case with
the information campaigns carried out in the field of road safety, where it is possible to read
slogans such as: "being vigilant is paying attention in order not to be taken by surprise",2 and
which, for example, place on the same level sleep deficit and mobile phone use at the wheel.
Vigilance-attention problems are today frequently identified in road accidents. However, the
impact of different processes at the root of these accidents is often confused and treated in a
global fashion, while these processes of vigilance and attention correspond to two groups of
very particular phenomena. From a perspective of operational action for the improvement of
road safety, it will therefore be necessary to better distinguish the issues of vigilance and
attention so that the measures that will allow mitigation of their disruptions will be very
different, sometimes even opposite.
In scientific language, notably in cognitive psychology, vigilance and attention are
considered as two groups of connected processes (one being the support for the other) but
each makes reference to specific mechanisms: vigilance qualifies the psychophysiological
state of activation of the nervous system; attention represents the state of concentration of
mental activity on a specific object. However, shortcomings in terms of vigilance and even
more in terms of attention have long been considered as secondary factors in accidents. It is
2
Information campaign "Road safety 2006, the 6th Parisian arrondissement gets mobilized" fact sheet n° 11.
Collective Expert Report
- 11 -
13/12/2011
only in the last twenty years or so that researchers' interest has turned to these issues. Firstly,
they have emphasized the impact of vigilance problems on the incidence of accidents, with
several medical teams working on the effects of fatigue and sleep deficit, particularly in
France. Their interest in the impact of attentional problems has developed slightly later,
partly linked to neurological disorders in drivers and partly linked to the eruption of new
information technologies at the heart of the task of driving.
Examination of scientific literature shows, however, that here too numerous clarifications are
required. In fact, the concepts used vary greatly between disciplines and from one author to
another, with definitions which are sometimes very different covering diverse processes.
Such conceptual heterogeneity thus leads to great variations in the data supposedly
qualifying the causes of accidents. If attempting to summarize the results from literature
(table 1.I), the conclusion drawn would be that vigilance problems contribute to between
1.8% and 54% of accidents (i.e. between almost none and half of cases) and that attentional
problems are involved in between 25.6% and 78% of cases, i.e. between a quarter and three
quarters of cases. This constitutes a range of data which is much too scattered to provide any
useful information. It is therefore necessary to distinguish between the processes that apply
to the concepts used.
Table 1.I: Variations in assessments of the impact of vigilance and attention related problems on
accidents
Factor
Vigilance related problem
Attention related problem
Occurrence in accidents (%)
1.8
References
Stutts et al, 2001
3
Pack, 1994; Sagberg, 1999
54
Dingus et al, 1987; Horne and
Meyner, 1995; Léger, 1995
35 to 50
Sussman et al, 1995
78
Neale et al, 2002
25.6
Wang et al, 1996
A preliminary distinction therefore immediately needs to be clearly established between
what results from a vigilance related problem, qualifying the body's non-specific activation
processes, and what corresponds to an attention related problem, identifying the processes
that condition the direction of the cognitive resources enabling the specific processing of
information (on this aspect, see the chapter 2 “Psychocognitive processes involved in driving
a road vehicle”). In fact, disruptions to these two sets of processes display very marked
differences in the root of accidents. The mobile phone constitutes a good indicator of the
need to clearly distinguish problems of vigilance and attention as its use can, in certain
conditions, favor deterioration in attentional processes and in other conditions (which are
undoubtedly more rare) favor an increase in alertness. Caseworks have in fact shown that an
additional task such as a mobile phone conversation is likely to stimulate vigilance during
long and monotonous periods of driving, in particular among professional drivers using the
highway at night (Olson et al, 2009).
Vigilance while driving
The notion of vigilance defines the psychophysiological variations of an individual's state of
alertness. It is characterized by a continuum ranging from the deepest sleep to the most
active wakefulness (Moessinger et al, 2006). This is typically described using the following
states, which correspond to different electroencephalographic rhythms: REM sleep, deep
Collective Expert Report
- 12 -
13/12/2011
sleep, light sleep, soporific, diffused wakefulness, active wakefulness, and hyperexcitation.
Vigilance processes are qualified as "non-specific", to the extent that they are not directed to
any particular aspect of the environment (contrary to attention processes) but qualify the
body's state, which will be more or less capable of processing the set of information in its
environment. Macworth's definition from 1950 clearly takes this into account: "Vigilance is a
state of preparation necessary to detect and respond to the smallest change appearing in the
environment at random time intervals".
However, it needs to be known that, contrary to received ideas, the link between the level of
vigilance and the effectiveness of the subject is not strictly linear: although a level which is
too low is always prejudicial, a level of vigilance which is too high can also be harmful,
depending on the task performed. This excess of vigilance, which represents stress or
hyperexcitation, will have a quicker power to deteriorate on complex activities than on
simpler activities (figure 1.2). There is therefore an optimal level of vigilance for each type of
task performed, and a deterioration in vigilance does not only represent drowsiness but may
also concern hypervigilance. However, a different optimal level is expected when a simple
task is to be performed than when the task is complex.
Figure 1.2: Yerkes-Dodson law concerning the link between levels of performance and levels of
vigilance (from Wickens and Hollands, 2000)
Furthermore, vigilance constitutes a "resultant" psychophysiological state, in the sense that it
is dependent on a whole set of diverse factors, both endogenous and exogenous, which
adjust it.
Factors in vigilance deterioration most often cited in literature are:
•
stressful or monotonous road situations (Liu and Wu, 2009);
•
fatigue (Lyznicki et al, 1998);
•
the circadian rhythm of vigilance (Klauer et al, 2006);
•
sleep and alertness disorders (McCartt et al, 1996);
•
driving time (Maycock, 1996);
•
individual characteristics such as age or physical condition (Milosevic, 1997);
•
consumption of psychotropes (Orriols et al, 2010).
It is necessary to emphasize the fact that each of these different factors can have an impact on
vigilance in isolation (for example a high dose of alcohol is enough to produce significant
deterioration); however, their involvement is often associated (even a low dose of alcohol can
Collective Expert Report
- 13 -
13/12/2011
have significant effects on the state of vigilance if combined with fatigue or lack of sleep)
(Howard et al, 2007; Vakulin et al, 2007).
Attention when driving
A certain level of alertness is thus indispensable in order to carry out any common task.
However, it is necessary to point out that this level of vigilance is, more often than not,
insufficient to correctly complete a task. The attention invested in an activity also strongly
influences performance. The notion of attention designates the set of processes that condition
the direction of an individual's cognitive resources towards a particular aspect of the
situation, with a view to the achievement of an objective (Richard, 1980). However, the study
of attention is made difficult by the multitude of processes that this concept covers, which
range from the selection of information to the resolution of conflict, via the mobilization of
attentional resources and attentional focalization. Today, an awareness of the problems of
attention at the wheel is observed in the milieu of road safety. These problems are very
widespread and affect the whole driving population; men and women, young and older
people. As previously mentioned, researchers' interest regarding this issue has in particular
been reinforced by the ever greater eruption of information technologies in the task of
driving.
Two essential characteristics of the workings of attentional processes are noted: the first
concerns the limited character of an individual's attention resources, while the second refers
to our ability to automate part of our processes.
Whatever the models considered, all the literature agrees on the fact that attentional abilities
are limited (Camus, 1996). The cognitive system cannot process an infinite amount of
information. When the cognitive demand increases to the point where it reaches the limit of
processing abilities, a cognitive overload is reached which is prejudicial to useful information
processing. In order to avoid this overload, the system must thus make decisions concerning
which information to process and which information must be disregarded: this is the
fundamental principle of attentional selection. Confronted with the complexities of the
information emanating from our environment, we will select the supposedly relevant
information for our objectives and, in exchange, inhibit the unselected information. In this
respect, the difficulty will be making the right choice between the most useful information
and the less important information.
Furthermore, in order to free up resources for tasks carrying a significant attentional burden,
the cognitive system also possesses the ability to automate some of the processes. Automatic
processes present contrary characteristics to those involved in controlled processes
(Schneider and Shiffrin, 1977). Controlled processes are slow, serial processes that require
consciousness and a large attentional burden. In contrast, automatic processes work in an
unconscious and uncalculated way. Above all, they present the advantage of consuming
very little attention (figure 1.3).
These automatisms develop following a consistent training of tasks which are sometimes
complex for a beginner and which comprise a certain degree of regularity. For example, the
set of operations necessary to get to making contact with the gearbox illustrates an
automated task well: complex to the point of mobilizing the basic cognitive resources of a
pupil at their first lesson, this operation will later take place almost autonomously, without
requiring the investment of attention. Based on repeated experience of situations, the
development of automatisms thus allows the limits of the system's capacity to be overcome,
thanks to the implementation of a parallel process that consumes fewer attentional resources.
However, the notion of an absence of attentional burden also means that certain actions can
be triggered in a non-optional and uncontrolled way; in other words, by automatisms. As a
general rule, the free rein of these automatisms is beneficial and efficient. However, in certain
cases, their release can act as a parasite on the process and provoke behaviors that are
Collective Expert Report
- 14 -
13/12/2011
inappropriate for the situation, due to the inflexibility of automated processes. (Van Elslande
and Alberton, 1997).
Figure 1.3: Characterization of automatic processes and controlled processes
Several consequences for cognitive performance can result from these characteristics, which
have a significant impact on carrying out the task of driving:
•
performance is contingent on the resources available for the task: the more
resources available for a task, the better the performance will be (this is evidently
subject to these resources being well invested in the task in progress);
•
performance of a task is contingent on the cognitive burden: the more processes
and resources a task requires, the more performance declines;
•
when two tasks are carried out simultaneously, if resources are transferred from
task 1 to task 2, performance of task 1 declines.
The automation of certain tasks, thanks to training, allows the freeing up of resources and
makes the system available for the completion of new tasks or tasks which cannot be
automated.
However, another side of this automation is that it can, in certain cases, bring about
undesirable effects, via an inappropriate triggering of automated behaviors, or simply by a
lack of the automatisms' adaptation to the characteristics of the situation.
We will now consider which of the various attentional disruptions can be identified in road
traffic accidents.
Attentional disruptions and accidents
Closely linked to the very significant variations in road situations, attentional disruptions
constitute complex problems, which are sometimes contradictory and have multiple sources.
Thus, in a real driving situation, the driver must ceaselessly divide his or her resources
between all potential sources of stimulation that emanate from his or her environment.
However, we recall that attentional capacity is, by definition, limited and that the driver
cannot remain 100% focused on the task of driving, as this would result in the driver quickly
becoming worn out. A "cognitive compromise", as defined by Amalberti (2001), is operated
between the demands of the task (adaptation to rules, safety, performance) and the interests
of the biological system (limiting the cognitive cost in order to conserve one's resources).
Attentional control therefore allows the distribution in time and space of the necessary
resources for each of these components, usually in the most suitable way. An attentional
problem arises either when the resources allocated to the task become insufficient in
proportion to the task's demands, or when the driver concentrates on one part of the
situation which is too narrow to resolve the problem. Thus, this imbalance in the distribution
Collective Expert Report
- 15 -
13/12/2011
of resources between the different sources of information, relative to their demands and
priorities, leads to various attentional failures. Most of the time, the dispersal of attentional
resources is not a problem in itself. On the contrary, it can be a synonym for cognitive
economy, and thus of efficiency in the given timeframe. It only becomes a potential cause of
accidents in certain situations, which it is important to precisely define. Improvements in
knowledge of the operator's cognitive functioning and the difficulties he or she encounters
during the displacement activity should thus allow the adaptation of the displacement
environment (in the broad sense of the set of elements that will mobilize attention) to the
operator's abilities to make the overall system safer.
Different shortcomings in attention when driving an automobile
Conceptually, today there still remains a terminological blur in literature on what is meant
by the terms attention, distraction and inattention. It is clear that there is no consensus
regarding these notions. For example, Regan et al. (2008) list no less than 14 definitions of the
notion of distraction.
Shortcomings in attention are generally considered as the result of interference between
different tasks (Lemercier and Cellier, 2008). This notion of interference refers to the
competition that can establish itself between two tasks, to the point of risking disrupting one
of the two. From an accidentological perspective, interference can be the product of
competition, either:
•
between a driving task and the thoughts or preoccupations of the driver, thus
referred to as inattention;
•
between a driving task (for example, interacting with traffic and the environment)
and a task separate from driving (for example, conversing with a passenger), thus
referred to as distraction;
•
between two driving tasks. For example: task 1 (seeking directions) and task 2
(interacting with traffic), or alternatively: task 1 (monitoring the overall road
scene) and task 2 (monitoring a potential risk identified in a certain component of
the situation and concentrating on it). Even if from a cognitive perspective this is
close to the notion of distraction (from one task by another), from an ergonomic
perspective of system adaptation, this will be referred to as competition for
attention.
Inattention
Certain authors (for example Regan et al., 2008) group all attentional disruptions behind the
notion of inattention and then categorize these disruptions into more specific types of
problems. Other authors (for example Van Elslande et al., 2009) reserve this term for when
taking account of shortcomings in attention that have an effect on the task in progress. Here
there is thus inattention to the road scene, which involves specific parameters and which will
also have specific accidentological consequences. The peculiarity of this form of disruption is
the absence of an external trigger; it only involves a reorientation of attentional control
towards one's thoughts (Lemercier et al., 2006). This phenomenon of inattention towards the
task of driving can have two main origins. It may be that inattention is linked to a lack of
demands by the task of driving, allowing the driver to become immersed in his or her
current thoughts and/or preoccupations. This is notably the case when a driver has a large
amount of experience of driving a certain route, or when this route is monotonous with few
mobilizing interactions, whether with the road or the traffic. In this case, attentional control
of the environment declines and the driving automatism is thus used in the sense of a
diversion of attentional resources towards the driver's own thoughts. Alternatively,
inattention may be linked to the fact that the driver is preoccupied with a personal problem,
Collective Expert Report
- 16 -
13/12/2011
creating a form of "cognitive distraction" capable of absorbing a part of available attentional
resources and limiting receptivity to external information.
Distraction
Distraction corresponds to the "capture" (voluntary or not) of the driver's attention by an
external element or event, which has no link to the task of driving, to the detriment of
monitoring the road scene. Stutts et al. (2003) studied the real-life driving of 70 subjects and
observed that drivers were engaged in one or more distracting activities during 16% of the
time when the vehicle was moving. In their study into the role of distractions to the driver in
road accidents, Stutts et al. (2001) distinguished approximately ten different sources (table
1.II). As this table illustrates, distracting activities can take very different forms, ranging from
conversation with a passenger to handling an object. But whatever the additional task, it
enters directly into concurrence with the task of driving to the point of being able to place the
driver in a double task situation (Lemercier et al., 2006) and therefore to diminish their
performances in the main task.
Table 1.II: Sources of specific distractions among drivers (Stutts et al., 2001)
Categories of distraction
% of drivers
Person, object or event outside the vehicle (any event
linked to traffic, encounters with pedestrians or
animals, etc.)
29.4
Adjusting radio, cassette, CD
11.4
Interaction with passengers in the vehicle (e.g.
discussion, turning towards a child in the back seat)
10.9
Movement of an object inside the car (which may be a
restless dog, a wasp, or an object falling under the
pedals, for example)
4.3
Use of an object brought into the vehicle (a CD, wallet,
bottle of water)
2.9
Adjusting air-conditioning
2.8
Eating or drinking
1.7
Telephoning
1.5
Smoking
0.9
Other distraction
25.6
Undefined distraction
8.6
Competition for attention
The different essential tasks involved in driving can enter into competition with one another,
which may or may not provoke interference disrupting the activity of driving. According to
the modeling of Alexander and Lunenfeld (figure 1.4), competition can be: vertical between
tasks of different hierarchical levels ("control of the vehicle", "interaction with traffic" and
"navigation") or horizontal between two tasks at the same level. Attentional resources must
therefore be distributed between these different sub-tasks within the task of driving in the
broad sense. Research works are found in the literature that employ the notion of distraction
in order to take account of this type of interference (Smiley, 2005). For example, a driver may
not have seen a vehicle travelling in front of him change lanes because he was "distracted" by
his use of the rear view mirrors to gain information. Or, even more paradoxically, he may
not have seen a vehicle coming from his left because he was "distracted" by the vehicles
coming from his right. However, it is clear that this refers not to an additional task to driving
Collective Expert Report
- 17 -
13/12/2011
which distracts the user, but to several components of the task of driving that the driver
must carry out in a coordinated way. From a "purely cognitive" point of view, these two
forms of disruption stem from similar mechanisms; they can therefore be studied
isomorphically in the laboratory. However, from an operational perspective, the problems
are different, and it is necessary to distinguish them in order to define the most suitable
procedures for action.
Figure 1.4: Horizontal and vertical competitions for attention between driving tasks (from
Alexander and Lunenfeld, 1986)
More generally, it is noted that by its very design, the activity of driving is made up of a set
of tasks carried out more or less simultaneously and which are sometimes in competition.
The cognitive effects of inattention, distraction and competition for attention can in certain
cases be very close, even alike. In fact, whether interference be linked to preoccupations, or
exterior to the task of driving, or directly linked to the task of driving, the resultant is the
same from a cognitive point of view: the driver finds himself in a double task situation. In
the three cases in the figure, attention is diverted from the main task. However, the
distinction that we make becomes necessary from an ergonomic point of view. Inattention,
distraction and competition for attention do not come from the same source and do not
appear in the same driving contexts. Above all, the operational solutions to be brought to
bear on these different problems of attention at the wheel are not identical, and are even
sometimes opposing (figure 1.5).
Figure 1.5: Connection between the processes of vigilance and attention (from Van Elslande et al.,
2009)
Collective Expert Report
- 18 -
13/12/2011
Mobile phone distraction
Interest in distraction at the wheel has experienced a marked increase with the arrival of the
mobile mobile phone. Research concerning the impact of mobile mobile phones on drivers'
performances has not stopped growing since the late 1990s, and is based on analysis of
experimental, accidentological and epidemiological data. The dominating trend that comes
out of all of this research works points to a deterioration in driving and an increase in the
risk of accidents linked to the use of mobile phones at the wheel. By analyzing nearly 700
accidents linked to the use of a mobile phone, Redelmeier and Tibshirani (1997) conclude
that talking on the mobile phone increases the probability of a collision between 3 and 6.5
times, thus conferring on telephonic distraction an impact on the risk of accident which is
close to that of alcohol. However, according to Sagberg (2001), the use of radio and CD
players causes even more accidents than mobile phones.
Generally, it has been shown that mobile phone conversations have a negative impact on
driving, even with a so-called "hands-free" device. This is explained by the mobilization of
cognitive resources, which is almost identical in the two cases during the period of
conversation. Horrey and Wickens (2006) show that mobile phone conversation has more
impact on response times when responding to road events than on the lateral control of the
vehicle. These results would be explained by the automation, or lack of it, of driving subtasks. Vehicle trajectory control is an automated activity, in comparison with the
identification of a danger which necessitates the mobilization of attentional resources.
However, the mobile phone is not only used for conversation. All operations linked to
mobile phone use which will involve mobilization of the whole set of attentional resources
(cognitive, visual, motor) will have a more significant deteriorating power, not only on
interaction with traffic but also on trajectory control, even though this is also automated
(Horrey and Wickens, 2006).
Use of a mobile phone while driving thus covers a set of parameters which can have very
different consequences. To simplify things, we will distinguish between two types of
distraction that are potentially generated by the mobile phone: a "purely cognitive"
distraction, which corresponds to the period of conversation; and an "integral" distraction,
which corresponds to all operations during which the diversion of attention is accompanied
by a diversion of the operator's gaze away from the road scene: looking for the mobile phone
or its accessories, dialing a number, reading/writing a message, etc. Every source of
distraction is potentially harmful from the point of view of driving, in the sense that it may
strain the attentional resource required to carry out the task. However, its distracting impact
will be closely related to a whole set of variables which merit clear definition. This will
enable identification of the conditions that will make driving problematic, in association with
the complexity of the situations encountered, the multiplicity of variables to process and the
consecutive calls on the individual's attentional resources. Due to the dynamic and temporal
constraints that characterize driving an automobile, the variability of possible situations, the
profusion of information to manage or, conversely, the monotony of certain situations,
driving an automobile is the most revealing indicator of the attentional difficulties that pose
themselves for the human being in his or her attempts to adapt to the activities confronting
him or her. Accidents bear witness to the limits of these abilities to adapt, which should not
be pushed to end by the challenges of unnecessarily complicated infrastructures, badly
presented information and speeds which are too high: i.e. everything that increases the
attentional burden. Mobile phone use constitutes a source of distraction, among others,
which punishes more or less severely depending on the situations encountered, the
characteristics of the conversation (long versus short, emotionally charged versus
informative), and above all depends on whether this use is accompanied by looking away
from the road scene and for how long.
Collective Expert Report
- 19 -
13/12/2011
However, accident data enabling the mobile phone to be considered as a major variable in
terms of road safety issues is still currently lacking. This is probably explained by the fact
that mobile phone use rarely has a single effect on the cause of an accident. Rather, it has an
impact on driving safety when it is combined with other parameters, in particular in an
encounter with an unexpected critical situation. Furthermore, mobile phone use is a
relatively brief event in relation to the length of driving time, and encountering critical
situations is rare. As a result, the combination of the two is a fairly rare conjunction. Added
to this explanation is the absence of systematic investigation into mobile phone use at the
moment an accident happens, leading to an underestimation of the stakes involved in the
issue. This is without forgetting the total lack of taking into account mobile phones which are
not held in the hand, which equates to ignoring half of all mobile phone use in accident data.
In conclusion, there is often a tendency in the field of safety, and in particular road safety, to
seek to locate the origin of problems with the system user, considering that traffic accidents
are the result of recklessness, incompetence and drivers' lack of skills (Gusfield, 2009), rather
than seeking more profound causes. The disadvantage of such a view is that it prevents
taking into account certain underlying, more organizational ("systemic") problems that
compound the difficulties faced by these users and as a consequence reduce their abilities to
control them (Wittingham, 2004). In-depth analysis of accidents (Van Elslande, 2003) shows
that they are often the product of complex interaction between human and contextual
factors, and are rarely the single effect of one among them all. Certain elements that are
innocuous in certain situations can become the cause of accidents in others. Thus, their
prevention involves acting on all of the considered system's components, within an optic of
favoring effective and safe actions by the component which acts at the end of the process: the
system user.
By its very nature, driving is one of those tasks for which attentional processes are
fundamental, and which requires a permanent adaptation of their resources within the
constraints of the encountered situation. Depending on the attentional burden required by
the encountered situation (complexity of infrastructures, multiplicity of interactions,
significance of unforeseen elements), mobile phone conversation can therefore, in the same
way as any additional task carried out while driving, strain part of the limited attentional
resources available to us, to the detriment of the driving itself. Furthermore, from an
operational road safety perspective, data from literature suggests the incomplete nature of
any measure limited to sanctioning the use of mobile phones held to the ear. Numerous
other levers can be used to help road users effectively manage their attentional resources. For
example, Kawano et al. (2005) have shown that good acoustic quality of reception can
strongly improve the safety of mobile phone use at the wheel, in the sense that greater
attention needs to be allocated to understand an audio signal whose deterioration makes
understanding of it more difficult.
Lastly, it is important not to create from mobile mobile phones an issue by which it is not
possible "to see the wood from the trees", in the context of multiple sources of disruptions to
attention that are generated by the driving environment itself, by unnecessarily complicated
infrastructures and by the movements and speeds of traffic that these generate, by
inadequate direction signage and by unnecessary sources of distraction (advertisements,
plethora of information). Every environment unnecessarily soliciting the individual's
resources carries in itself a latent source of dysfunction. Also, by association with other
elements (like looking for directions, dense traffic, the least source of distraction within or
outside the car), latent dysfunction can manifest itself in driving failure.
Collective Expert Report
- 20 -
13/12/2011
BIBLIOGRAPHY
ALEXANDER G, LUNENFELD H. Driver expectancy in highway design and traffic operations.
Publication FHWA-TO-86-1, Federal Highway Administration: Washington, DC, 1986
AMALBERTI R. La conduite de systèmes à risques. Presse Universitaire de France, Paris, 2001
CAMUS JF. La psychologie cognitive de l’attention. Armand Colin, Paris, 1996
DINGUS T, HARDEE H, WIERWILLE W. Development of models for on-board detection of driver
impairment. Accident Analysis and Prevention 1987, 19: 271-283
ELGAROV A. Road crashes and alcohol abusage in Kabardino-Balkaria. Proceedings of the 13th
International Conference on alcohol, drugs and driving safety, 1995, 2: 741-743
ELVIK R, VAA T. The handbook of road safety measures. Elsevier Science, Oxford, 2004
GUSFIELD J. La culture des problèmes publics. L’alcool au volant : la production d’un ordre
symbolique. Chicago, Economica, 2009
HOLLNAGEL E, AMALBERTI R. The Emperor’s new clothes or whatever happened to ‘human
error’? 4th International Workshop on human error, safety and system development. Linköping, June
11-12-2001
HORNE J, MEYNER L. Sleep related vehicle accidents. BMJ 1995, 310: 565-567
HORREY J, WICKENS C. Examining the impact of cell phone conversations on driving using metaanalytic techniques. Human Factors: the journal of human factors and ergonomics society 2006, 48: 196-205
HOWARD ME, JACKSON ML, KENNEDY GA, SWANN P, BARNES M, PIERCE RJ. The interactive
effects of extended wakefulness and low-dose alcohol on simulated driving and vigilance. Sleep 2007,
30(10): 1334-1340
KAWANO T, IWAKI S, AZUMA Y, MORIWAKI T, HAMADA T. Degraded voices through mobile
phones and their neural effects: A possible risk of using mobile phones during driving. Transportation
Research Part F: Traffic Psychology and Behaviour 2005, 8: 331-340
KLAUER S, DINGUS T, NEALE V, SUDWEEKS J, RAMSEY D. The impact of driver inattention on
near-crash/crash risk: an analysis using the 100-Car Naturalistic Driving Study data. N° DOT HS 810
594. National Highway Traffic Safety Administration, Washington, DC, 2006 LEGER D. The cost of
sleepiness. Sleep 1995, 18: 281-284
LEMERCIER C, CELLIER JM. Les défauts de l’attention en conduite automobile : inattention,
distraction et interférence. Travail Humain 2008, 71: 271-296
LEMERCIER C, MOESSINGER M, CHAPON A. Inattention. In : Contribution du groupe Attention au
livre Blanc de Réseau, Eveil, Sommeil, Attention, Transport. CHAPON A, GABAUDE C, FORT A
(eds). 2006, 40-42
LEPLAT J. Analyse cognitive de l’erreur. Revue européenne de psychologie appliquée 1999, 49: 31-41
LIU Y, WU T. Fatigued drivers driving behavior and cognitive task performance: Effects of road
environments and road environment changes. Safety Science 2009, 47: 1083-1089
LYZNICKI J, DOEGE T, DAVIS R, WILLIAMS M. Sleepiness, driving and motors vehicle crashes.
Journal of the American Medical Association 1998, 279: 1908-1913
MACKWORTH N. Researches in the measurement of human performance. MRC special report series
n°268, HM stationary office, London, 1950
MAYCOCK G. Sleepiness and driving: the experience of UK car drivers. Journal of Sleep Research 1996,
5: 229-231
McCARTT A, RIBNER S, PACK A, HAMMER M. The scope and nature of the drowsy driving
problem in New York state. Accident Analysis and Prevention 1996, 28: 511-517
MILOSEVIC S. Drivers’ fatigue studies. Ergonomics 1997, 40: 381-389
MOESSINGER M, CHAPON A. Introduction : clarification des concepts. In : Défauts d’Attention et
Conduite Automobile : état de l’art et nouvelles orientations pour la recherche dans les transports.
CHAPON A, GABAUDE C, FORT A (eds). INRETS synthesis n°52, Paris, 2006, 11-14
Collective Expert Report
- 21 -
13/12/2011
NEALE V, KLAUER S, KNIPLING R, DINGUS T, HOLBROOK G, PETERSEN A. The 100 car
naturalistic driving study, phase I–experimental design. Report NHTSA, Washington, DC, 2002
OLSON R, HANOWSKI R, HICKMAN J, BOCANEGRA, J. Driver distraction in commercial vehicle
operations. Report No FMCSA-RRR-09-042, 2009, Washington, DC, USDOT, FMCSA
ORRIOLS L, DELORME B, GADEGBEKU B, TRICOTEL A, CONTRAND B, et al. Prescribed
medicines and the risk of road traffic crashes: results of a French registry-based study. PLoS Med 2010,
7: e1000366. doi:10.1371
PACK AI. Obstructive sleep apnea. Adv Intern Med 1994, 39: 517-567
REDELMEIER D, TIBSHIRANI R. Association between cellular-mobile phone calls and motor vehicle
collisions. New England Journal of Medicine 1997, 336: 453-458
REGAN M, LEE J, YOUNG K. Driver distraction: Theory, Effects and Mitigation. CRC Press, Florida,
USA, 2008
RICHARD JF. L’Attention. PUF, Paris, 1980
SAGBERG F. Road accidents caused by drivers falling asleep. Accident Analysis and Prevention 1999,
31 : 639-649
SAGBERG F. Accident risk of car drivers during mobile mobile phone use. International Journal of
Vehicle Design 2001, 26: 57-69
SCHNEIDER W, SHIFFRIN R. Controlled and automatic processing: behavior, theory, and biological
mechanisms. Cognitive Sciences, 1977, 27: 525-559
SMILEY A. What is distraction? Paper presented at the First International Conference on Distracted
Driving, 2005, Toronto
STUTTS J, REINFURT D, STAPLIN L, RODGMAN E. The role of driver distraction in traffic crashes.
Report prepared for AAA Foundation for Traffic Safety, 2001, Washington, DC
STUTTS J, FEAGANES J, RODGMAN E, HAMLETT C, MEADOWS T, et coll. Distraction in everyday
driving. Report prepared for AAA Foundation for Traffic Safety, Washington, DC, 2003
SUSSMAN E, BISHOP H, MADNICK B, WALKER R. Driver inattention and highway safety.
Transportation Research Record 1995, 1047: 40-48
VAKULIN A, BAULK S, CATCHESIDE P, ANDERSON R, et coll. Effects of moderate sleep
deprivation and low-dose alcohol on driving simulator performance and perception in young men.
Sleep 2007, 30: 1327-1333
VAN ELSLANDE P. Erreurs de conduite et besoins d’aide : une approche accidentologique en
ergonomie. Le Travail Humain 2003, 66: 197-226
VAN ELSLANDE P, ALBERTON L. When expectancies become certainties: a potential adverse effect
of experience. In: Traffic and transport psychology: theory and application. ROTHENGATTER JA,
CARBONELL VAYA E (eds). Pergamon Press, Oxford, 1997
VAN ELSLANDE P, JAFFARD M, FOUQUET K, FOURNIER JY. De la vigilance à l’attention :
influence de l’état psychophysiologique et cognitive du conducteur dans les mécanismes d’accidents.
INRETS report n°280, 2009
WANG JS, KNIPLING R, GOODMAN M. The role of driver inattention in crashes: new statistics from
the 1995 Crashworthiness Data System. 14th Annual Proceedings of the Association for the
Advancement of Automotive Medicine, 1996, Vancouver, BC
WHITTINGHAM R. The blame machine: why human error causes accidents. Elsevier, Oxford, 2004
WICKENS C, HOLLANDS J. Engineering psychology and human performance. New Jersey, Prentice
Hall, 2000
Collective Expert Report
- 22 -
13/12/2011
2
Psychocognitive processes involved in driving a road
vehicle
Driving an automobile is a complex task that requires perceptive, motor and cognitive skills.
On the cognitive plane, the driver must select the most pertinent information for the road
task from the multiple elements of information coming from the road situation, and then
respond with actions appropriate for the situation.
The ability to select the pertinent information for the action in progress has been studied in
cognitive psychology in the context of attention theories. More recently, the ability to choose
suitable actions has been developed as part of executive function theories, notably influenced
by neuropsychology. Executive functions can be defined as enabling adaptation to new
situations by the programming of a sequence of events adapted to achieve an aim. But these
attentional and executive functions are closely intertwined, insofar as the selection of
information is guided by the needs of the action to be carried out.
Consequences of using the mobile phone on the task of driving have been studied on the
cognitive plane, in the context of attention theories and in double task situations, and more
broadly in multiple task situations. The first section of this analysis will refer to the models
developed in cognitive psychology in order to define and understand the phenomena of
attention and the ability to carry out double tasks. The contribution of research on double
tasks to understanding the consequences of mobile phone use at the wheel will also be
addressed.
Laboratory-developed models are enriched by their comparison with cognitive ergonomics
studies on complex work activities. Furthermore, the activity of driving an automobile
involves motivation and risk management. The contribution of these different models to
understanding the phenomenon of mobile phone use at the wheel is debated.
Attention and double task situations
Attention
Attention is certainly not a unitary concept. As underlined by William James, one of the
fathers of modern psychology, in his book "Principles of Psychology" at the end of the 19th
century (1890): "Every one knows what attention is. It is the taking possession by the mind,
in clear and vivid form, of one out of what seem several simultaneously possible objects or
trains of thought." Understanding the phenomena of attention was thus addressed by the
earliest theoreticians of psychology, who only made use of introspection. This method is now
considered too subjective, as it refers only to one's own conscious experiences.
Cognitive psychology and its methods
Since the 1950s, psychology has become a scientific discipline combining, as with many other
scientific disciplines, experimental methods based on observation and development of
theoretical models. Cognitive psychology aims to study the mechanisms enabling an
individual to review or his or her environment and the achievement of actions in that
Collective Expert Report
- 23 -
13/12/2011
environment. It studies functions such as memory, language, attention and the programming
of actions. For cognitive psychology, the mind is conceived as an information processing
system. In order to understand the workings of this system, this discipline has developed
theories or models of cognitive functioning. These theoretical models are designed on the
basis of inferences supported by observational data on the behavior of people in certain
"experimental" situations created in the laboratory. This laboratory work enables all the
environmental factors and the characteristics of the actions to be carried out in a given
situation to be controlled. By modifying certain parameters in a given situation, it is possible
to verify if the behaviors expressed in this situation correspond to the behaviors predicted by
the theoretical model being tested. Experimental situations constitute simplifications of real,
more complex situations. This simplification is indispensable to the devising of theoretical
models. In order to examine the ability of laboratory-developed models to reflect real
situations, it is advisable to evaluate the parameters that are not taken into account and their
possible roles in cognitive functioning in the most complex situations.
A cognitive function model is supposed to reflect all acquired knowledge on a phenomenon
or function at a given moment. The non-specialist might be surprised by the existence in
scientific literature of several theoretical models to summarize, for example, attention
focalization, or the double task effect. However, the diversity and competition between these
models contribute to their development: experimental comparisons of different models
advance research. Understanding the concepts in this field is often made difficult by the use
of different terms for notions that appear closely related. When developing theoretical
models, the vocabulary adapts itself to developments in the understanding of the
phenomena, but it can also reflect its scientific discipline of origin. In fact, models developed
in neighboring disciplines cross over throughout this field: experimental cognitive
psychology as we have already defined it; cognitive ergonomics which has to take account of
complex activities such as those in the world of work and/or aeronautics; and
neuropsychology, which has to take account of the effect of cerebral lesions on cognitive
functioning. Comparing different disciplines favors the emergence of models enabling
understanding of complex behaviors in automobile driving situations and their multi-task
aspects.
Attention, notions of selectivity and distraction
The study of attention continues to mobilize the scientific community of psychology.
Attention is central to cognitive functioning as it plays a part in the modulation of other
functions. One of the important characteristics of attention is selectivity, illustrated in the
earliest research by Broadbent's filter theory (1958): the processing system was conceived as
a filter through which only one piece of information could pass at a time. Later research has
shown that this concept of a single channel for information processing has to be well
qualified. Attention can be divided between several perceptual elements of a single task, or
between perceptual elements relating to two different tasks. The quantity of information that
can be taken into account at a given moment by the processing system is therefore larger
than suggested by the earliest models, but the notion of selectivity is not called into question.
In many situations, an individual receives a large amount of information from the
environment or from his or her own body. Selective attention enables selection of only the
information which is pertinent to the task in progress. This process of focusing attention on
pertinent information is closely linked to the process of suppressing irrelevant information.
For some authors, the notion of distraction corresponds to a failure of the process of
suppressing elements of information that are irrelevant to the task in progress. For example,
a driver can be distracted while driving because a poster advertisement, or an event taking
place on the side of the road, will automatically attract his or her attention. This can prevent
the driver focusing their attention on the elements to be considered in order to correctly
process the task of driving and by consequence can lead to errors in the management of the
Collective Expert Report
- 24 -
13/12/2011
road situation. The source of the distraction can be external to the person, as in the previous
example, or can be internal: it can involve signals from the body that divert the driver's
attention, for example a sudden pain, or thoughts that may interfere with the processing of
information.
Attentional capacity and central processor notions
In the 1970s, the idea of a single processing channel, initially advanced by Broadbent, was
abandoned in favor of a model of capacity or resources. Kahneman (1973) described, within
the information processing system, the existence of a central processor with the role of
assigning attention to the various elements of the perceptual situation.
According to this model, all activity requiring attention is in competition with other potential
activities. When available attentional resources are insufficient for the demands of the task,
the level of performance declines. In order to qualify the level of consciousness and attention
required for the realization of a task, Kahneman introduced the idea of "mental effort", which
has remained a central concept in all current theories. Certain tasks require little mental
effort while others require a large amount. The central processor's capacity is flexible in
conjunction with the individual's intentions of the moment, long-term motivational factors
and the biological pertinence of perceptual elements, but also in conjunction with the
attention demanded by the task (thanks to a feedback loop) (figure 2.1).
Figure 2.1: Kahneman's "central processor" model (1973)
This concept of attention in terms of capacity or resources was completed by the distinction
between automatic processes and controlled processes (Schneider and Shiffrin, 1977). A
"controlled process" demands much in the way of attentional capacity, is slow and of a serial
nature (a single input is processed at one time), is conscious and can easily be altered by the
subject. It is affected by processing demands which are produced at the same moment.
Conversely, an "automatic process" demands little in the way of attentional capacity, is rapid
and parallel (several inputs can be processed at the same time). It is unconscious, difficult to
change or suppress and is little affected by other processing demands being produced at the
same time. Automatic processes correspond to routines learned by repetition of the same
task.
Collective Expert Report
- 25 -
13/12/2011
This distinction between automatic and controlled processes facilitates understanding of
how certain routines can be carried out with little conscious intervention and attentional
resources. However, automatic and controlled processes represent two extremes of a
continuum. Both types of process play a role in complex activities such as automobile
driving.
Double task situations
Research on the double task paradigm has developed since the 1970s and shows that in
certain circumstances, attention can be divided between several elements of a situation, or
between two different tasks. But this is far from always being the case.
Engaging in a second (secondary) task when already involved in a first (principle) task
constitutes a source of distraction. Processing the information necessary to manage the
secondary task interferes with the processing of the information necessary to deal with the
principal task. As a general rule, research has shown a decrease in the quality of performance
when two tasks are carried out at the same time in comparison with the separate execution of
a task. However, the consequences of a double task situation on performance depend on the
characteristics of the tasks involved.
This research has confirmed the operational range of the distinction between automatic and
controlled processes, as it has been shown that interference between two tasks carried out at
the same time depends on the level of automaticity of each task. If both tasks call on
controlled processes, the negative interference on performance is significant, while it is very
limited when at least one of the two tasks calls on automatic processes. This is illustrated by
the results of a study by Sullivan (1976): the subjects had to repeat words going into one ear
while a message was communicated to the other ear at the same time. If the message was
more complex (more complicated words or sentences) the subjects' performance in repeating
the words declined.
Performing a double task also depends on the level of expertise for each task. For example,
Spelke and colleagues (1976) asked subjects to read short stories that they had to understand
while writing down words being dictated. At the start of the experiment, the participants'
reading time was considerably extended as a double task. But after 6 weeks of practice, they
were reading as quickly (understanding what they were reading) during the double task as
they were during the single task. This effect of expertise on double tasks is directly linked to
the fact that experience enables the setting up of routines or automatisms to process the task,
thus reducing the mental effort involved. Logan (1988) developed the instance theory of
automatization, according to which automatization is mnestic recovery: performance is
automatic when it is based on recovery of direct memory access and in a single stage.
Interference between tasks depends on the sensory inputs used. Negative interference on
performance is stronger if both tasks use the same sensory input. Shaffer (1972) showed that
if subjects have to type words presented visually and repeat a message going into one ear,
the level of performance of the tasks is comparable to that of tasks carried out separately. But
when both messages are aural, (same sensory entry channel) or must be read (same sensory
entry, same motor exit), performance carrying out the two tasks declines.
On the basis of these results, Wickens (1980) made the idea of resources more complex by
developing the theory of multiple resources in which different stocks of resources are
defined in a model with three modalities. The first modality differentiates visual and aural
resources, the second differentiates resources in terms of spatial or verbal response and the
third modality analyses the three phases of information processing: perception, central
processing and response. According to this theory, competition for resources would take
place only if the two tasks involved the same parts of each modality. The idea that
interference between two tasks depends on the stage of information processing of each task
Collective Expert Report
- 26 -
13/12/2011
is of particular interest in this theory, as it implies that interference depends on the temporal
coordination of the carrying out of the two tasks.
Experimental proof that interference linked to double tasks is part of the sensory domain or
effector used links to the notion of specialized processing modules developed at the same
time in neuropsychology, according to which different processes are effected by different
specialized modules (Fodor, 1983). This idea is produced from the observation that certain
cerebral lesions disrupt certain cognitive processes and not others, and in this way are
selective. According to this, a functional independence exists between diverse processing
modules. However, this so-called "modular" approach cannot reflect all cognitive
functioning, in particular when it concerns attention processes and cognitive control
processes.
Cognitive models
All current cognitive models combine a modular approach and the notion of a central
processor, which has an indispensable control function for the coordination and coherence of
the action in progress.
The most influential model in neuropsychology is that of Norman and Shallice (1986)
(figure 2.2). This model considers that the majority of information processing operations are
executed without attentional control, in the form of acquired programs which are
automatically triggered by appropriate signals.
The model's base units (or diagrams) are units of knowledge which control overlearned
sequences of action or thought (for example: carrying out a home-work commute). These
diagrams are activated either by perceptual information from the external environment, or
by information from the internal environment (from the individual himself or from other
diagrams). Once triggered, the action diagram continues to operate until the aim of the
action is reached, or until its suppression by competing diagrams or by a superior control
process. "Management of priorities" in the sequence of events ensures the coordination of the
most pertinent diagrams for the desired aim. In particular, its role enables management of
competition between the different diagrams that could potentially be activated. The
supervisory attentional system (SAS) intervenes in all situations where the selection of
routines is insufficient, in particular when responding to new situations. Cerebral lesions, in
particular in the frontal cortex, can disrupt this system.
Figure 2.2: Cognitive model by Norman and Shallice (1986)
Collective Expert Report
- 27 -
13/12/2011
The other model that remains very influential in cognitive psychology and neuropsychology
is Baddeley's working memory model, initially devised by Baddeley and Hitch in 1974 and
modified by Baddeley in 2000. This model complements the one by Norman and Shallice
which mainly treats action selection. The notion of working memory suggests that it takes
account of processes which allow individuals a mental representation of their immediate
environment and short-term retention of useful information for the pursuit of a goal. This
model was inspired by Shriffin and Atkinson's "short-term memory" model (1969) which
describes how diverse information processed in parallel by different sensory registers leads
to short-term registration, as a mandatory passage to long-term memory and the formation
of memories. The notion of "working memory" emphasizes the dynamic aspect and the
intervention of attention in this process.
Baddeley's model (2000) is made up of 4 components: the central executive and three
systems which temporarily store information (figure 2.3). The phonological loop and the
visuo-spatial sketchpad specialize respectively in verbal and visuo-spatial information
storage, while the "episodic buffer" is capable of integrating information from diverse sources
(the phonological loop and the visuo-spatial sketchpad, but also information coming from
the long-term memory, the so-called "episodic memory") to bring all information together to
form a single representation. The central executive controls the whole system by dividing
attention between these components, and Baddeley attributes it with a role comparable to
that of the SAS in Norman and Shallice's model.
Figure 2.3: Baddeley's "central executive" model (2000)
Double task research contribution to the problem of mobile phone use at
the wheel
Using the mobile phone while driving constitutes a double task. If the driver's principle task
is to drive while avoiding having an accident, then mobile phone use at the wheel can be
considered a source of distraction. The elements of information necessary to process the
secondary task that is the mobile phone conversation will interfere with processing the
information for the principle task, i.e. driving.
By taking into account current cognitive models and research carried out in cognitive
psychology on the double task, it is possible to predict that the secondary task of
"telephoning" will interfere with the principle task of "driving" in two different ways:
•
when the two tasks call on the same sensory module: as the task of driving always
includes a visual element, if the driver has to divert his or her gaze towards the
mobile phone, for example to write an SMS text message, this would be more
detrimental than if the telephony task only involves the auditory or vocal channel;
Collective Expert Report
- 28 -
13/12/2011
•
when one of the two tasks, or both, calls on "attentional resources" or, in other
words, requires "mental effort".
Concerning the second point, being an experienced driver should facilitate the double task:
experienced and competent drivers have a significant number of automatisms and routines
available to them to manage the road situation and require less attentional resources in
numerous conditions.
It is important to take into account the existence of individual differences in the availability
of attentional resources: these depend on the individual's cerebral state. In fact, a double task
is more difficult for older people and even more so for people presenting certain
neurological diseases.
The availability of attentional resources, in one driver alone, can vary according to alertness
and the time of the journey. Kahneman's model (1973) had already shown that one of the
factors affecting the capacity of the central processor, and thus of attentional resources, was
the body's state of alertness, affected by the sleep-wake cycle. This state of alertness, or
vigilance, can be reduced if an individual is lacking sleep (night driving) or suffers from
sleeping disorders. Vigilance may also be reduced in monotonous driving situations, when
the absence of information to process is no longer feeding the feedback loop which raises the
level of vigilance.
For the same individual, the availability of attentional resources can also vary according to
the state of cognitive fatigue, linked to the depletion of attentional resources. A single driver
can dispose of attentional resources at the beginning of a journey, but these resources can
rapidly decrease in the context of a busy road.
Driver operating models and complex activity models
Some authors have brought into doubt the ability of laboratory-developed cognitive theories
to reflect the complexity of the automobile driving situation.
Models of drivers' cognitive functioning have been developed by integrating the results of
cognitive ergonomics research on complex activities.
Rasmussen's model (1986, SKR Skill-Rule-Knowledge model) differentiates three levels of
behavior:
•
behavior based on knowledge, which is conscious, non-automatic and
requires attentional resources;
•
behavior based on rules. This is also conscious and intervenes when performance
of a task involves the automatic activation of rules through which a sequence of
subroutines is effected;
•
behavior based on routines which do not involve conscious processes.
This model is very close to that of Schneider and Shriffin (1977) and opposes automatic and
controlled processes. It introduces an intermediate level, that of rules, which remains
conscious even though the development of the action is based on acquired knowledge.
Michon's hierarchical model (1985) differentiates three levels of decision making:
•
at the strategic level, decisions concerning general journey planning including the
choice of road, strategies for avoiding traffic jams or minimizing journey time, and
departure time;
•
at the tactical level, decisions concerning maneuvers to be carried out to negotiate
driving situations, such as intersections and slip roads;
Collective Expert Report
- 29 -
13/12/2011
•
at the operational level, decisions concerning actions for the basic control of the
vehicle, such as braking or changing lane. The three levels involve different time
scales, time pressure permanently existing at the operational level.
Other authors have highlighted that the driving situation, which is complex and dynamic,
involves motivation and risk management. Wilde (1982) puts forward his "risk homeostasis
theory". This considers that risk cannot be eliminated but most be optimized. Each driver
will adopt an acceptable level of risk that takes into account the advantages and
disadvantages of the options associated with an increase or decrease in risk. Summala (1988)
also puts forward a theory whereby a driver in a dynamic driving situation controls "safety
margins". This author posits the existence of subjective risk or a "fear monitor" which
influences the driver's decisions when his or her safety margins are exceeded.
Fuller (2005) challenges this notion of risk avoidance and substitutes the theory of mental
effort avoidance. According to this theory, the driver will apply the law of least effort
regarding employment of attentional resources. The driver thus tends to privilege the use of
routines and means that enable him to reduce the activity of driving's mental burden when it
becomes too complex. Reducing car speed is one of the means privileged in order to reduce
the mental effort linked to driving; consequently, the increase in mental effort linked to
mobile phone use at the wheel should translate into an adjustment/a reduction in car speed.
This idea of mental effort avoidance is also central to the models developed to reflect
complex activities, such as that by Hoc and Almaberti (2007). This model integrates a
metacognitive level, "metacognitive control", the role of which is to distribute control
between a control (or symbolic) mode and an automatic (or sub-symbolic) mode with the
aim of fully controlling the situation. It rests on the hypothesis that optimal use of cognitive
control paradoxically consists of setting performance to a sub-optimal level. This level is
satisfactory in terms of responding to the perceived needs of the situation while preserving
the capacity to carry out activities in parallel (work or thoughts) and by allowing effective
work in the long term (economy of resources). Freedom of resources through cognitive
compromise therefore has the objectives of guaranteeing a stable performance at the same
time as avoiding draining resources and furthermore being able to invest efforts in parallel
activities.
In conclusion, research into attention and more specifically research into double task
situations carried out in cognitive psychology shows that capacity to carry out two tasks
simultaneously depends on the characteristics of the tasks concerned and the availability of
attentional resources.
The more specific models of drivers' behavior highlight the need to take into account the
driver's motivation and risk management. Other models highlight the idea that the driver
has a tendency to privilege the use of routines learned by experience in his or her behavior,
thus attempting to minimize the mental effort necessary and therefore the employment of
attentional resources.
However, it is not possible to determine from current scientific literature how drivers
conform to these types of models when using the mobile phone at the wheel. The research
that has been carried out does not enable a conclusion to be drawn as to whether mobile
phone use leads to behavioral adjustments in the task of driving that facilitate a reduction in
risk or the attentional resources available to not be overloaded. Nor does this research assist
in understanding if there are individual differences in the implementation of these possible
behavioral adjustments, for example linked to age, driving experience, gender or drivers'
personalities.
Collective Expert Report
- 30 -
13/12/2011
BIBLIOGRAPHY
BADDELEY AD, HITCH GJ. Working memory. In: Recent advances in learning and motivation.
BOWER GA (ed). Vol. 8, New York, Academic Press, 1974: 47-90
BADDELEY AD. The episodic buffer: a new component of working memory? Trends Cogn Sci 2000, 4:
417-423
BROADBENT D. Perception and communication. Oxford, Pergamon, 1958
FODOR J. Modularity of mind. Cambridge MA, MIT Press, 1983
FULLER R. Towards a general theory of driver behavior. Accident Analysis and Prevention 2005, 37: 461472
HOC JM, ALMABERTI R. Cognitive control dynamics for reaching a satisfying performance in
complex dynamic situations. Journal of Cognitive Engineering and Decision making 2007, 1: 1-34
JAMES W. Principles of Psychology. New York, Henry Holt, vol.1, 1890
KAHNEMAN D. Attention and effort. Englewoods cliffs, NJ, Prentice hall, 1973
LOGAN GD. Toward an instance theory of automatisation. Psychological Review 1988, 95: 492-527
MICHON JA. A critical review of driver behavior models: What do we know, what should we do? In:
Human behavior and traffic safety. EVANS L, SCHWING RC (eds). New York, Plenum press, 1985:
221-236
NORMAN DA, SHALLICE T. Attention to action: willed and automatic control of behavior. In:
Consciousness and self-regulation. DAVIDSON RJ, SCHWARTZ GE, SHAPIRO D (eds). New York,
Plenum, 1986: 1-18
RASMUSSEN J. Information processing and human-machine interaction. 1986. Amsterdam, Elsevier
SCHNEIDER W, SHIFFRIN RM. Controlled and automatic human information processing. 1.
Detection, search and attention. Psychological Review 1977, 84: 1-66
SHAFFER LH. Multiple attention in continuous verbal tasks. In: Attention and performance. Vol. 5.
RABBIT PMA, DORNIC S (eds). London, Academic Press, 1972
SHIFFRIN RM, ATKINSON RC. Storage and retrieval processes in long term memory. Psychological
Review 1969, 76: 179-193
SPELKE E, HIRST W, NEISSER U. Skills of divided attention. Cognition 1976, 4: 215-230
SULLIVAN L. Selective attention and secondary message analysis: A reconsideration of Broadbent’s
filter model of selective attention. Journal of Experimental Psychology 1976, 28: 167-178
SUMMALA H. Risk control is not risk adjustment-The zero-risk theory of driver behavior and its
implications. Ergonomics 1988, 31: 491-506
WICKENS C. The structure of attentional resources. In: Attention and Performance. VIII.
NICKERSON R (ed). Hillsdale, NJ, Erlbaum, 1980: 239-257
WILDE GJS. The theory of risk homeostasis: implication for safety and health. Risk Analysis 1982, 2:
209-225
Collective Expert Report
- 31 -
13/12/2011
3
The impact of mobile phone use on the driving activity
The development of in-vehicle information and communication systems multiplies causes of
distraction for the driver. Using these systems generates situations where tasks are added to
the task of driving, which are not without consequences in terms of road safety. When
considering the impact these systems on the driving, it is necessary, first of all, to
differentiate between those whose first objective is to act as a driving aid to improve safety,
and those without a safety objective. In order to evaluate the distraction engendered by an
assistance system, such as a navigation system, it is necessary to weigh up the beneficial
effects that it could have on driving against the inattention that results from its use. In the
case of a system such as the mobile phone which does not ordinarily have any safety
objective, only a distracting effect can be expected.
A distinction also imposes itself between systems and functions. A navigation system, for
example, besides guiding the driver also gives him or her additional information, such as the
time or distance until the destination or the position of speed cameras. Similarly, the mobile
phone can also assume different functions (e.g. sending/receiving SMS text messages,
consultation of internet services) in addition to verbally communicating with an interlocutor.
Furthermore, even when it is used within a conversation, the latter necessitates the
realization of different actions such as dialing a number, holding the line and finally
conversing, which will not all have the same impact on driving. A significant amount of
experimental research on the impact of the mobile phone on automobile driving has focused
on the effect of a phone conversation proper. Such researches have been carried out in
laboratories, on driving simulators or the open road.
Effect of the mobile phone on capturing and processing road information
Many researches have shown the importance of processes for selecting and processing
information while driving. In fact, looking the wrong way at a critical moment and/or not
seeing an important element in the road environment can have dramatic consequences when
driving.
Selecting information
Important modifications to visual behavior have been observed among drivers when talking
on the mobile phone at the wheel. It has thus been shown that drivers look straight ahead
more and neglect checking their peripheral field, notably rear view mirrors and control
instruments such as the speedometer (Pachiaudi, 2001; Recarte and Nunes, 2000 and 2002;
Harbluk et al., 2007; Pereira et al., 2010). In particular, intersections are less well inspected
(Harbluk et al., 2007; Pereira et al., 2010). Harbluk et al. have shown, in real driving
conditions, that the frequency of looking towards traffic lights reduces at intersections (some
drivers even neglect them completely), as with inspecting areas situated to the right.
In the same way, thanks to use of eyetrackers which allow precise registration of ocular
movements, it has been proven that there is a reduction in the variability of the gaze's spatial
direction (or the gaze's concentration) towards the road's central zone when drivers carry out
Collective Expert Report
- 32 -
13/12/2011
cognitive tasks such as talking on the mobile phone (Recarte and Nunes, 2000 and 2003;
Nunes and Recarte, 2002; Victor et al., 2005; Harbluk et al., 2007; Engström et al., 2005). For
Recarte and Nunes, registered visual fixations are longer and the visual field reduces both
horizontally and vertically during the carrying out of cognitive tasks.
This phenomenon of gaze concentration associated with the poorest consultation of the
peripheral field reveals a change in strategies for collecting visual information and,
according to Victor et al. (2005), can finally reveal that when telephoning a driver prioritizes
control of his or her trajectory, to the detriment of other driving sub-tasks. These authors do
however emphasize that drivers, even when phoning, adapt their ocular behavior depending
on the complexity of the driving task (differences are shown between sections of straight
road and bends in rural areas).
Furthermore, Recarte and Nunes (2003) have shown that gaze concentration generated by
the practice of mental activity at the wheel is accompanied by a significant reduction in
detection performance. In real driving conditions, drivers had to react to spots of light
appearing on the windshield and inside the vehicle, by pressing on buttons positioned on the
wheel. Their results showed that the percentage of correctly detected targets reduced
significantly when the driver was carrying out a cognitive task. However, for these authors,
this deterioration in the detection of targets is not necessarily a consequence of the gaze
concentration mentioned above. Rather, it is linked to the diverting of attentional resources
towards the cognitive task to the detriment of the driving task, which prevents the optimal
involvement of top-down processes. This deterioration in detection performance is also
shown in other studies (Strayer and Johnston, 2001; Hancock et al., 2003; Törnros and
Bolling, 2005; Bruyas et al., 2009).
Information processing
Research from Strayer and colleagues (Strayer et al., 2003; Strayer and Drews, 2007a and b)
attempted to explain the perceptual deficits registered when a driver carries out a cognitive
activity. As an explanatory framework, they put forward the hypothesis of "inattentional
blindness" caused by the action of talking while driving. As a consequence of this
inattentional blindness, even when a driver looks directly at an object, they cannot see it;
they "look but fail to see", because their attention is diverted towards a context other than that
of driving. For this, they developed a series of experiments (Strayer et al., 2003; Strayer and
Drews, 2007a and b) using "surprise" recall tests of elements present in the driving
environment. Participants drove in a simulator without knowing that they would be asked to
remember these objects. Their results showed that during a mobile phone conversation
drivers are less likely to create a lasting memory of encountered objects (half as many
elements were recognized during the test), whether these objects were relevant to driving or
not.
Using electroencephalograms (EEGs) to record the brain's electrical activity, and more
specifically recording the event-related brain potentials generated by road scene events,
enabled these authors (Strayer and Drews, 2007a and b) to better understand the
mechanisms involved. These brain waves, and more precisely P300 component, are linked to
attentional processes and make it possible to estimate the "quantity" of attention allocated to
a task, by giving indications on the temporality of the processing of signals, notably
concerning detection, discrimination and categorization processes. The fact that a reduction
in P300 amplitude during phone conversations is observed also shows that if the mnestic
trace of encountered objects is less durable, it is not the result of a difficulty in recovering the
information at the point of the recall test, but the consequence of an interference at the point
of the initial encoding of the information coming from the road scene. Little semantic
analysis of these objects has been carried out at the point of the encoding of the information.
Collective Expert Report
- 33 -
13/12/2011
In other words, it seems that talking on the mobile phone while driving affects the way in
which drivers pay attention to a stimulus in the driving environment.
By using the same technique, Bruyas et al. (2006) have shown that the reduction in the N200P300 complex amplitude was also linked to the complexity of the communication task. The
more complex the communication, the more appreciable this reduction, which witnesses to a
more important reduction in the resources allocated to the driving task.
Another methodological framework has been proposed by McCarley et al. (2004) in order to
better understand these phenomena, with the paradigm of "change blindness". The ability to
perceive changes in the visual environment is essential if one wishes to maintain an
acceptable performance in a complex environment. Sometimes, significant changes occur
that are not noticed, notably if they occur during an interruption, even if of a very short
duration. Such interruptions can be natural (ocular saccades) or provoked by using an
experimental device. McCarley et al. have thus shown that a natural mobile phone
conversation disrupts detection of changes in complex static road scenes. Two photographs
were presented, alternatively separated by a mask, and participants had to detect the change
introduced in the second image. Eye-tracking data showed that even if the modified regions
were focused on, whether in a single or double task, changes are less frequently detected in a
double task. The authors explain this result in part by an impairment in oculomotor search in
the phone condition and, in agreement with Strayer et al. (2003) and Strayer and Drews
(2007a), by a deficit in the encoding of the information at the point of fixation. As expected,
the changes that have a bearing on relevant objects are better detected than those that have a
bearing on irrelevant objects in a single task; however, this benefit linked to the relevance of
objects is eliminated in double task conditions, demonstrating a change in the efficiency of
oculomotor search. On the other hand, ocular fixations are shorter in a double task, which
would probably not allow sufficient encoding of visual information. However, the authors
highlight that this phenomenon cannot explain by itself the changes encountered in terms of
detection, as Strayer and colleagues (2007) showed that the process was defective, even when
controlling the length of fixation.
Effect on driving performance
Much research has been carried out in this field, in particular during the last two decades.
This has been synthesized by meta-analysis by Horrey and Wickens (2006) and by Caird et
al. (2008). The principle of meta-analysis allows the combination of different studies testing a
common hypothesis, in order to estimate the breadth and validity of observed phenomena
and then to accept or reject said hypothesis. In this case, it is deterioration in driving
performance that is being measured while using the mobile phone at the wheel, compared to
a control condition of driving without a mobile phone. Horrey and Wickens (2006) listed
approximately 50 experimental studies carried out between 1991 and 2004 centered around
the effect of a mobile phone conversation on driving, and selected 23 of these for their metaanalysis. Caird et al. (2008) enumerated more than 100 such studies in 2008, of which 33
satisfied their required criteria for carrying out their meta-analysis.
Two large families of variables were studied in particular: the driver's reaction time to
different types of signals, which is where most studies are found, and the parameters
enabling description of vehicle dynamics such as lateral control, following distances and
speed variations. Researches carried out in this field has also tried to demonstrate the
possibility of drivers' adaptive behavior, such as increasing following distances or reducing
speed, but the obtained results are divergent.
Collective Expert Report
- 34 -
13/12/2011
Response time
According to Green (2000), the variable which most affects reaction time is anticipation. A
driver who is fully aware of the appearance time and the location of a signal can step on the
brake pedal in 0.75 seconds. This takes almost twice as long if the signal is unexpected: the
intrusion of a common signal (rear light of the vehicle ahead, for example) would require
1.25 seconds; while the intrusion of an unexpected signal (an interfering object in the way)
requires 1.5 seconds to brake. The quantity of attentional resources allocated to the driving
task is also a very important factor in analyzing reaction time.
The meta-analyses cited above agree that there is a significant cost of phoning for driving
performance, expressed in terms of reaction time for an event or stimulus. According to these
meta-analyses, the results indisputably show that drivers' response time increases when they
use the mobile phone at the wheel. Horrey and Wickens (2006), as well as Caird et al. (2008),
also show that the size of effects is comparable when results are obtained on driving
simulators as well as in real driving conditions.
Furthermore, Harbluk et al. (2007) observed, in real driving conditions, that drivers carry out
more hard braking (longitudinal deceleration exceeding 0.25g 3 ) when engaged in a difficult
mobile phone task. Hancock et al. (2003) also observed, on a track, that distracted drivers
brake more sharply when they have to stop at a red light than they do when they are not
distracted. More precisely, drivers begin to press on the brake later, but compensate for this
late pressure by braking harder, in order to ultimately obtain a shorter stopping time. The
number of stops at red lights also decreases: from 95% without distraction, decreasing to 80%
with distraction. Harbluk et al. (2007) suggest that the reduction in visual control of the
environment effected by a driver who is phoning (see above) could partly explain this
adjustment to braking behavior. In order to brake in a suitable manner, the driver must effect
a control of the environment which allows him or her to take all pertinent information into
account. When the driver is distracted, recognition of these elements is distorted, which
delays the moment of decision-making. In this case, sharper braking compensates for this
delay.
Vehicle dynamics
According to the meta-analysis carried out by Caird et al. (2008), talking on the mobile
phone does not appreciably affect neither lateral control nor following distances. In fact, the
impact is minimal and, above all, differs according to studies. However, these authors do
indicate that studies are few and sometimes contradictory. For example, for Alm and Nilsson
(1995), drivers who use the phone do not compensate for the increase in their reaction times
by increasing their following distances; whereas, for Strayer et al., (2003), they increase their
distance from the vehicle in front, whether traffic is dense or not. In both these cases, the
studies were carried out in simulated driving conditions. Lamble et al. (1999) took collision
time as their reference, meaning the time necessary for a vehicle to collide with a vehicle
ahead, if they maintain a constant course and speed. Conversely, they showed that this
collision time reduced when the driver was using the mobile phone at the wheel.
As Horrey and Wickens (2006) emphasize, the fact that the impact of the mobile phone is
expressed more in terms of an increased response time than in terms of lane keeping is
explicable. Lane keeping is a relatively automatic skill that requires few attentional
resources. Responding to a signal is less automatic as the driver not only has to detect this
signal, but also has to select a sequence of appropriate actions to respond to it. Nevertheless,
certain studies have shown that lateral control could be improved during phone
communications (Engström et al., 2005; Törnros and Bolling, 2005; Pereira, 2009). In fact,
lane keeping is closely linked to the direction of the driver's gaze. The spatial concentration
3
1g = 9.8 m/s2
Collective Expert Report
- 35 -
13/12/2011
of the gaze towards the center of the lane observed when drivers carry out cognitive tasks
could also lead, in certain cases, to better maintenance of the vehicle on the lane.
The possibility that drivers compensate for the increase in response times brought about by a
phone conversation by reducing their speed has also been evaluated. Here again, the results
are divergent. While certain studies show a reduction in speed when drivers converse using
a hands-free phone (Fairclough et al., 1991; Haigney et al., 2000; Rakauskas et al., 2004;
Cooper et al., 2009), others show a reduction in speed only when using a hand-held phone
(Burns et al., 2002; Patten et al., 2004; Törnros and Bolling, 2005 and 2006). Traffic can also
play a role: speed only decreases when traffic is moderate to heavy, and not when it is light
(Cooper et al., 2009); along with the length of the call: speed decreases for professional calls
lasting less than 11 minutes and increases when they are longer (Rosembloom, 2006). We
note that, in this last case, the results were obtained on the road from 34 drivers who did not
know that they were being observed. According to Caird et al.'s meta-analysis (2008), drivers
who use a hand-held phone reduce their speed more than those who use a hands-free one
(see "Hands-free/hand-held" section).
Decision-making
The majority of experimental studies have focused on the impact of mobile phone
communications on components of the driving task, such as braking time and control of the
vehicle's trajectory and its dynamics. Very little research has been carried out into the effects
of mobile phone use on more tactical or strategic aspects or decision-making.
The first research that showed the deleterious effect of a mobile phone conversation on a
driver's ability to make a decision was carried out by Brown et al. (1969) on a trial track. The
drivers had to pass through gateways of various widths. When a gateway was judged to be
too narrow, they took a bypass lane. Their misjudgments were much more numerous during
phases of phone communication.
Later, interactions between drivers in the course of phoning and other road users were
observed in real driving conditions by Anttila and Luoma (2005). These authors showed that
carrying out an auditory task disrupts the way in which drivers interact with other road
users, in particular at intersections. They recorded an increase in unnecessary hesitations
before committing to the situation and dangerous behavior by distracted drivers, as well as
an increase in inappropriate behavior towards vulnerable users (pedestrians or cyclists), with
the latter being forced to stop in order to avoid a collision, for example. These situations
were even more frequent when carrying out cognitive or auditory tasks, compared to
carrying out tasks of a visual nature.
Other authors have subsequently investigated lane changes in simulated driving conditions.
Cooper et al. (2009) explored the influence of mobile phone conversation on unrestrained
driving behavior: drivers were authorized to change lane as many times as they wanted. The
number of lane changes was significantly lower during conversations, in particular when
traffic was moderate to heavy. Similar results were obtained by Beede and Kass (2006) who
also showed that drivers committed a significantly higher number of violations (exceeding
speed limits, failing to stop at red lights, crossing solid lines) and a significantly higher
number of errors that were qualified as attentional errors (insufficient inspection of an
intersection, stopping in the absence of a stop sign or at a green light or going before a green
light) during phone conversations. By making the decision to change lane less frequently,
drivers prioritize their trajectory: they avoid the less important driving sub-tasks in order to
allocate more attentional resources to the dual task of phoning and driving. As Beede and
Kass (2006) highlight, behavior that avoids the completion of certain tasks but in the course
of which a higher number of errors and violations is recorded supports a deterioration in
Collective Expert Report
- 36 -
13/12/2011
situation awareness, 4 as drivers no longer succeed in processing all information in the road
environment. This reduction in situation awareness during phone communication has also
been observed by Gugerty et al. (2004). By showing videographic scenes to drivers, these
authors have shown that phone communication degrades various aspects of their situation
awareness, including their abilities to identify and respond correctly to dangerous events
and to avoid accidents.
Mobile phone use also affects drivers more in situations requiring complex decision making,
such as turning left (across traffic), than in situations where decision making is more simple,
such as stopping at a red light. Cooper et al. (2003) exposed drivers to different driving
situations on a track, while they had to listen and respond to relatively complex messages.
The extent to which the deterioration in driving performance occurred in dual task
conditions was shown to depend on the complexity of the maneuver. In more common
situations, such as reacting to traffic lights, drivers were able to put into place adaptation
strategies which allowed them to successfully stop when necessary, even in dual task
condition. This was not the case in more complex situations such as turning left with oncoming traffic. The impact of divided attention situations was even shown to be worsened in
poor driving conditions, on wet roads, preventing drivers from carrying out the necessary
adjustments in order to correctly manage interaction with other vehicles; decision-making
thus proved to be more risky.
Comparison with other verbal and auditory activities
The impact of a mobile phone conversation on driving behavior has been compared to the
practice of other verbal and auditory activities such as listening to the radio or talking to a
passenger. It was established that all auditory tasks do not modify the driving performance
in the same way.
Phoning and listening to the radio
Several studies have compared the effect of listening to the radio with that of a mobile phone
conversation on driving performance. In contrast to the phone condition, no influence on
response time was observed when drivers listened to the radio (Strayer and Johnston, 2001;
Consiglio et al., 2003; Bruyas et al., 2006). For Recarte and Nunes (2003), only tasks involving
the production of a verbal response have an effect on visual research and the ability to detect
and select the response. Tasks limited to listening to verbal material, such as the radio, affect
neither visual behavior nor detection. For these authors, receiving information in the form of
neutral messages, which are without emotive overtones and which do not require an
immediate action to be carried out, do not disrupt the driving task. Similar results were
obtained by McCarley et al. (2004), who showed that there was a deficit in participants'
capacity to detect changes in real-life road scenes when they were talking on a hands-free
phone, but this type of deficit was not observed if they were listening to other participants'
pre-recorded conversations.
These different studies show that listening to vocal material is insufficient, in itself, to
generate interference with the driving task. In the absence of real engagement with a verbal
activity, which is generally the case when listening to the radio, no deterioration in the
driving is observed. It is understood that the attentional demand could vary depending on
the program being listened to and, above all, differs from handling the radio controls.
4
The concept of situation awareness introduced by Endsley (1995) defines three levels of awareness: the perception of
environmental elements, the understanding of their meanings and the anticipation of their future evolution. Reaching these
three levels is considered as good awareness of the situation.
Collective Expert Report
- 37 -
13/12/2011
Kunar et al. (2008) have attempted to specify at what level this interference is situated
between the two tasks. They used a tracking task, consisting of following circles in motion,
and tested two conditions of word production. First of all, they showed that a mobile phone
conversation alters the time it takes to respond to the tracking task, while simply listening to
a story does not. Furthermore, the tracking task is altered when the subjects generate words
from heard words but it is not altered if they simply have to repeat these words. These
authors conclude that the interference observed is not located at the motor level of language
production, but at the level of the cognitive processes necessary for carrying out a discussion.
Only the most complex tasks interfere and not purely motor tasks such as repeating words.
Such results can be linked to those obtained by Bruyas et al. (2009). In a simulated study, the
effect of communication which had been made asynchronous by using an answering
machine was evaluated. The resulting communication was divided into three parts: listening
to the message, producing the response and the different phases of interaction with the
system. The three phases did not have the same effect on driving behavior, expressed here in
terms of signal detection and response time. The most disruptive phases, corresponding to
the longest response times and the most numerous detection errors, were those phases
producing a verbal response, during which the engagement of the driver was the most
important. Use of such an answering machine could be advantageous to driving as it places
communication under the driver's control, which is not the case with a mobile phone
conversation: for one thing, the driver can listen to the message again as many times as he or
she likes and, for another, he or she can choose the best moment to respond, for example
after having finished a maneuver. Moreover, response phases are very short, which confers
another type of advantage on this sort of answering machine over a mobile phone
conversation.
Talking on the mobile phone or to a passenger
The question of whether it is more dangerous to talk on the mobile phone or with a
passenger is debated. Several studies have attempted to compare the effects on driving of a
mobile phone conversation and of a conversation with a passenger. First of all, it should be
remembered that a conversation, whatever it is, places the driver in a dual task situation
which, de facto, has a potential effect on driving. In this respect, the meta-analysis by Caird
et al. (2008) revealed an almost equivalent cost in terms of response time between the two
tasks.
Some of the earliest research comparing the two tasks was carried out by Fairclough et al.
(1991). For these authors, talking on the phone increases the cardiac rhythm more than
talking with a passenger, a result that they explain partly by their drivers' inexperience of
using the mobile phone at the wheel, which could have generated additional stress; phone
use at the wheel was in fact marginal at that time. However, they put forward the hypothesis
that a mobile phone conversation could be more demanding in terms of attention than
talking with a passenger. Later, Consiglio et al. (2003) discovered a slight but fairly non
significant increase in response time between conversations with a passenger and mobile
phone conversations. The authors note that these results, which were obtained in a
laboratory, could have been different in real-life driving situations as drivers could adapt the
flow of their conversations depending on the situation, which would be easier to do with a
passenger than on the mobile phone. Research by Drews et al. (2008) confirmed this
hypothesis and showed that the two types of conversation differ because surrounding traffic
can become a subject of conversation, which helps the passenger and driver to share the
same awareness of the situation and consequently mitigate the negative effects of the
conversation on the task of driving. Crundall et al. (2005) supported this hypothesis by
showing that the rhythm of a conversation with a passenger changes depending on the
road's demands, a phenomenon that they called 'conversation suppression'. Driver and
passenger naturally interrupt the conversation when the driving situation becomes more
Collective Expert Report
- 38 -
13/12/2011
complex, which cannot happen during a phone conversation. However, Horrey and
Wickens' meta-analysis (2006) does not seem to support this idea. For Horrey and Wickens,
the two types of discussion have a similar cost for driving performance. This suggests that
passengers, at least in the studies considered, do not change their conversation in a way that
reduces the cost. However, these results must be interpreted with caution, given the few
studies taken into account.
Gugerty et al. (2004) studied the effect of conversations on drivers' situation awareness. Their
results showed that processing of road information deteriorated in both cases. However, the
authors suggested that when a driver becomes very engaged in a mobile phone
conversation, he or she can encounter more difficulties to shift his or her attention away from
this task and over to the driving task when necessary.
Other studies have shown that the two types of conversation have a different effect on
driving. Drews et al. (2008) evaluated different measures of driving performance reflecting
the operational, tactical and strategic levels of driving (cf. Michon's model, 1985). They
observed greater variability in trajectories, greater following distances, and a greater number
of navigation errors during mobile phone conversations than during conversations with a
passenger. They explain the latter result by referencing the hypothesis of inattentional
blindness (Strayer et al., 2003 and 2007). Drivers did not process enough information coming
from the road environment when phoning, whereas when talking to a passenger the latter
was likely to compensate for this deficit.
During a simulated driving experiment, Hunton and Rose (2005) observed that phone
conversations were associated with a higher number of driving errors and "accidents" than
conversations with a passenger. For these authors, phone conversations require more of the
driver's attentional resources, which is detrimental to the task of driving. These results are
consistent with those of Charlton (2009) who, also in a simulated driving experiment,
obtained a higher rate of accidents among drivers on the mobile phone compared to those
who were talking to a passenger.
In order to attempt to better understand the differences between the two types of
conversation, several studies have analyzed variations in conversations, in both conditions.
While driving, a greater deterioration in the quality of speech is observed during mobile
phone conversations compared to conversations with a passenger. Fewer words are spoken
per minute (Gugerty et al., 2004), whereas the amount of hesitation and repetition is higher
(Bruyas and Taffin, 2009), as well as the number of errors (Laberge et al., 2004).
The complexity of the driving task also has a negative impact on the quality of speech: the
average length of utterance decreases (Crundall et al., 2005) and the amount of hesitation
increases (Bruyas and Taffin, 2009), as does the number of repetitions (Laberge et al., 2004)
while the complexity of the speech uttered in terms of syllables per word decreases (Drews
et al., 2008; Laberge et al., 2004).
The fact that speech is more affected by mobile phone conversations could reveal a higher
attentional demand by the phone task. Two reasons could explain this. The first reason is
linked to the absence of the interlocutor. A phone conversation requires additional cognitive
resources from the driver, in order to compensate for the lack of non-verbal indicators
present in a face to face situation (Alibali et al., 2001). For the interlocutor, a lack of
information on the surrounding traffic is added to this lack of feedback; a situation which
does not allow the interlocutors to adapt their cooperation. We note, however, that the
attitude of passengers could play an important role, as this cooperation with the passenger
can become a disadvantage if the passenger is inconsiderate or aggressive. In this case, the
psychological distance imposed by the mobile phone may even prove beneficial!
At the same time, a conversation with a passenger is regulated by the driver and can be
interrupted if the attentional demand of driving increases (Crundall et al., 2005). On the
Collective Expert Report
- 39 -
13/12/2011
other hand, the pace of a mobile phone conversation is directed by an expectation of
continuity. By analyzing conversations obtained in real-life driving conditions, Bruyas and
Taffin (2009) have shown that drivers' overall verbal flow is equivalent whether they talk to a
passenger or on the mobile phone. However, when hesitations or fillers are excluded and
only real words are counted, this verbal flow is lower in the case of phone conversation.
Such a result expresses this need to ensure the continuity of the conversation: as silence
could potentially be misunderstood by the interlocutor, the driver fills the gaps by
multiplying hesitations and repetitions. A similar process is described by Drews et al. (2008)
who observed that drivers continued speaking more often on the mobile phone than with a
passenger, an effect that they interpreted as a need to dominate the conversation in order to
avoid engaging in a process of understanding. It is clear that such processes require
significant cognitive effort.
Together, these results finally show that attentional demand could be much more higher in
the case of a mobile phone conversation than in the case of a conversation with a passenger.
Hands-free or hand-held mobile phones
Does the use of a hands-free mobile phone have the same effects on driving as the use of a
hand-held mobile phone? Several studies have attempted to measure the effects of the two
types of phone on driving (Haigney et al., 2000; Burns et al., 2002; Consiglio et al., 2003;
Patten et al., 2004; Törnros and Bolling, 2005; Strayer et al., 2006; Hendrick and Switzer,
2007). The mental workload induced by their use and the effects on driving performance are
the most often investigated parameters.
In all cases, maintaining a mobile phone conversation while driving increases the mental
workload, but that is comparable whatever the phone used, according to Patten et al. (2004)
in an experiment carried out in real traffic conditions and according to Törnros and Bolling
(2005) in an experiment carried out in a driving simulator. Both authors used a Peripheral
Detection Task. This task, which is considered as an indirect indicator of the mental
workload, consists of detecting diodes on the windshield and pressing a button when they
light up. Results showed that response time to these diodes was higher during phone
communications, but this was comparable for both types of phone. Equivalent results were
obtained with a measurement of heart rate, which increased in both cases (Haigney et al.,
2000). However, we note that in another experiment, Burns et al. (2002) obtained different
results in a driving simulator, drivers having judged the attentional demand to be higher
when the mobile phone was hand-held than when it was hands-free.
First of all, driving performance has been evaluated in terms of response time. As before,
response time increased when the driver used the mobile phone at the wheel, but no
difference was recorded whether the phone was hands-free or hand-held (Strayer and
Johnston, 2001; Burns et al., 2002; Consiglio et al., 2003; Strayer et al., 2006; Hendrick and
Switzer, 2007); this result is confirmed by the meta-analyses of Horrey and Wickens (2006)
and Caird et al. (2008).
Regarding the lateral control of the vehicle, study by Törnros and Bolling (2005) did not
reveal a difference between the two types of phone. These authors observed a slightly better
maintenance of the lateral position when drivers were using the mobile phone, as was shown
above. However, this result differs from study by Haigney et al. (2000) who observed a
higher number of deviations from the route in a driving simulator when the mobile phone
was hand-held, and from results from Burns et al. (2002), for whom neither type of phone
had any effect on lateral control of the vehicle.
The differences between the two types of phone seem highest in terms of speed. A significant
reduction in speed is observed when the mobile phone is hand-held (Burns et al., 2002;
Collective Expert Report
- 40 -
13/12/2011
Patten et al., 2004; Törnros and Bolling, 2005 and 2006) or, according to Haigney et al. (2000),
for both phone modes. There are two possible explanations for this phenomenon of speed
reduction. These results could reveal an adaptation of driving behavior aiming to reduce the
mental workload brought about by using the mobile phone while driving in order to keep it
at an acceptable level. Ultimately, this could explain that the mental workload is comparable
in both cases. However, while it is important to highlight the possibility of setting up such
adaptive behavior, Patten et al. (2004) insist on the fact that it may not be enough to
compensate, totally safely, for the reduction in attention accorded to the task of driving.
Another explanation of this reduction in speed lies in the fact that drivers could be more
aware of the negative effects on driving of a distraction brought about by a manual task,
such as holding a mobile phone in the hand, and underestimate this distraction, if it is only
cognitive, with a hands-free phone.
These results show that the effects on driving behavior of a conversation using a hand-held
phone versus a hands-free phone do not seem to be very different, whether these are
expressed in terms of mental workload or in terms of driving behavior. An exception to this
is speed, which is sometimes reduced in the case of hand-held phones; this result is
confirmed by meta-analysis (Horrey and Wickens, 2006; Caird et al., 2008). However, authors
insist on the fact that the negative impact of a hand-held phone could be exacerbated in
situations requiring manual intervention by the driver (for example turning at an
intersection). Thus, as emphasized by Consiglio et al. (2003), this does not mean that handsfree phones are not advantageous in certain situations, but it is clear that a hands-free kit
cannot resolve all the attentional problems linked to mobile phone use at the wheel.
Talking and handling a mobile phone
Besides talking to an interlocutor, using a mobile phone involves the realization of diverse
tasks, such as dialing, answering and hanging up. Other functions are also available, such as
reading or writing SMS text messages, or consulting the numerous services available on the
internet. The previously mentioned studies were focused on the effect of cognitive tasks such
as talking on the phone and excluded handling proper. Tasks of a visual-manual nature will,
obviously, have different effect on the driving.
Effect of visual-manual tasks on driving
Firstly, carrying out a visual task while driving does not have the same effects on drivers'
visual behavior as carrying out an auditory or cognitive task. A visual task necessarily
induces a diversion of the gaze towards the device being used, bringing about a momentary
interruption to the processing of information coming from the road environment. Victor et
al. (2005) have shown that, when driving, the time spent looking at an in-vehicle display
increases with the complexity of the visual task to be carried out: glances are more
numerous, last longer on average and the number of glances lasting longer than two seconds
increases. At the same time, the phenomenon of concentration of the gaze towards the center
of the road, observed during the carrying out of auditory tasks, can intensify with visual
tasks, when the gaze comes back to the road after consulting the device. The authors thus
recorded not only a loss of information linked to the diversion of the gaze towards the inside
of the vehicle, but also a deterioration in the gathering of information, similar to that
observed for tasks of a cognitive nature.
The realization of visual-manual tasks also has various repercussions on driving
performance. Firstly, a greater increase in response time for detecting signals and a greater
decrease in the number of signals that were correctly detected were observed during phases
of dialing compared to phases of mobile phone conversation (Törnros and Bolling, 2005).
Collective Expert Report
- 41 -
13/12/2011
This was the same during the realization of secondary tasks (including phases of dialing)
requiring a visual-manual interface, compared to when these same tasks were carried out
with a vocal interface (Ranney et al., 2005).
In terms of lateral control, the repercussions of visual-manual tasks are especially negative.
Briem and Hedman (1995) showed an increase in lateral position deviations during handling
of radio controls. These deviations are also higher than those observed during
communications. Comparable results were obtained by Törnros and Bolling (2005) during
phases of dialing, by Ranney et al. (2005) during the realization of different visual-manual
tasks including dialing tasks, and by Tsimhoni et al. (2004) when entering destinations in a
navigation system.
As shown by Engström and colleagues (2005), the direction of the gaze is strongly linked to
lane keeping, and the more the driver looks away from the road, the more his or her position
in the lane deteriorates. The time sharing necessary for carrying out a visual-manual task
while driving leads to intermittent control of the environment, during which the driver
strives to maintain an acceptable lane keeping performance by reducing speed and/or by
making large corrections with the steering wheel; in contrast with auditory tasks which lead
to a concentration of the gaze towards the center of the lane and are associated with better
performance in lane keeping. For Jamson and Merat (2005), the deterioration of the lane
keeping performance seems even higher when the visual-manual task is complex, while the
reverse is observed for auditory tasks: the more complex the task becomes, the less the lane
performance deteriorates. It is at this level that the most important differences between the
effects of visual-manual tasks and cognitive or auditory tasks on driving performance reveal
themselves. Caird et al. (2008) also highlight that holding and/or handling a mobile phone or
keypad requires the use of a hand, which generates a biomechanical interference with
steering and add to lateral vehicle control difficulties.
However, authors have highlighted some forms of adaptation by drivers to these situations
of shared attention. In a driving simulator, Horberry et al. (2006) showed that drivers reduce
their speed more when handling their car radio controls or inserting a cassette than when
they talk on the mobile phone. For Ranney et al. (2005), they increased their following
distance when using an interface, whether manual or vocal, even if they had been instructed
to maintain a constant distance. Similar results were obtained by Tsimhoni et al. (2004): when
entering a destination, drivers reduced their speed, whatever the mode used (manual or
vocal), and the highest following distances were revealed in manual mode (use of a
navigation system keypad). Another study carried out by Lansdown et al. (2004), looked at
conflicts of information that could be caused by simultaneous interaction with several
systems, situations where a driver had to carry out several added tasks while maintaining
safe control of the vehicle. They recorded a reduction in speed during the realization of
visual-manual tasks, whether they were carried out simultaneously or not. Following
distances were, however, shown to be significantly reduced during the realization of a single
secondary task, but the authors noted a non significant increase when drivers carried out
two secondary tasks simultaneously. Such behaviors aiming to reduce speed or to increase
headway are interpreted as attempts by drivers to reduce the additional attentional demand
brought about by the realization of these visual-manual tasks.
Effect depending on the type of interface: visual or auditory
Comparisons have been made between the effect of voice dialing and manual dialing
(Jenness et al., 2002). Drivers deviate more often from their lane when manually entering a
number than in control conditions without dialing; there is no significant difference between
voice dialing and control conditions without dialing. At the same time, an equivalent
reduction in speed is made by drivers for both modes, in order to compensate for the
additional attentional demand; however, this compensation is not sufficiently effective to
Collective Expert Report
- 42 -
13/12/2011
maintain a low rate of driving errors in manual mode, as witnessed by the increased number
of lane deviations recorded.
This advantage of voice dialing over manual dialing was also highlighted by Salvucci et al.
(2002) and by Ranney et al. (2005). Furthermore, the voice mode is equally advantageous
over the manual mode for entering a destination in a navigation system (Tsimhoni et al.,
2004). The time necessary to enter an address while driving is shorter than when drivers use
a keypad, and the observed deterioration in lateral control is less. Lastly, drivers consider
keypad use to be more difficult than the voice mode.
Sending and receiving SMS text messages
Few studies have focused on the effect on driving of sending or receiving SMS text messages
(Drews et al., 2009; Hosking et al., 2009). Reading or writing an SMS text message requires a
diversion of the gaze towards the mobile phone; the two studies cited do not mention a
difference between the two activities. Taking account of the age of the population studied
(18-21 years for the study by Hosking et al., 2009 and 19-23 years for the study by Drews et
al., 2009), it is likely that the drivers participating in the study were very used to practising
this type of activity, including while at the wheel. Also, writing an SMS text message may be
an automated activity among these drivers, which could explain this lack of difference, given
that no automaticity can be involved in reading this type of message.
For Hosking et al. (2009), retrieving and writing SMS text messages strongly disrupts visual
exploration of the road environment: drivers look more often and twice as long inside the car
than in control conditions (without SMS text messages). This time spent not checking the
road environment has, clearly, consequences in terms of driving performance. A
deterioration in the driving control is recorded, with more numerous lane excursions and
greater variability in the lateral position than in control conditions. However, drivers
compensate for these difficulties by increasing their following distance. Study by Drews et al.
(2009) confirms these results. These authors used a task where drivers followed a vehicle on
a highway, also in a driving simulator, and had to brake every time the vehicle they were
following braked. A significant increase in response time was recorded between control
conditions and dual task conditions, and in equivalent reaction time when the driver read or
wrote an SMS text message. As before, at the same time a deterioration in driving
performance was observed in terms of lateral control and longitudinal control. While an
increase in average following distances was observed, a greater variability in these distances,
along with shorter minimum distances, has also been recorded. This result conveys an
attempt on the part of drivers to reduce the risk of an accident linked to carrying out the
double task, but this attempt is not truly effective as the number of collisions remains higher
in double task conditions than during a single task. Comparing these results with data
previously obtained in the same conditions with mobile phone conversations (Cooper and
Strayer, 2008), the authors showed a much higher deterioration in driving performance for
reading and writing SMS text messages than for a phone conversation. They concluded that
reading and writing SMS text messages while driving could be more dangerous than many
other distracting activities that drivers could engage in.
Limits of experimental research
While experimental studies are an excellent paradigm for studying the behavior of drivers in
a controlled environment, certain limits to these studies should be indicated. In the majority
of these studies, whether carried out in a driving simulator or in real-life driving conditions,
the management of the driving task, as with management of distracting tasks, is often
determined by the experimenter and not by the driver. The latter must follow instructions
Collective Expert Report
- 43 -
13/12/2011
and has few margins for maneuver in order to adapt his or her behavior to the situation.
Nevertheless, we note that some adjustments have been recorded in certain cases, such as
reductions in speed or an increase in following distances.
The driving task, in itself, is not always very representative of natural driving, in particular
in regards to laboratory-based experiments or experiments in a driving simulator. In fact,
different realities are found when a driving simulator is used. Sometimes involving a simple
tracking task with an approximation at following a trajectory (principally designed as
laboratory-based experiments), the term 'simulator' can refer to a variety of devices, the
realism of which will, evidently, be more or less different. Although more realistic,
experiments on the road also induce a certain bias, which is linked to driving an unfamiliar
vehicle and a lack of motivational factors. The fact that the driver, knowing that he or she is
being observed, tries to drive as well as possible, and that the evaluated situations are
generally not emergencies, can lead to the assumption that the results obtained are
sometimes optimistic. Lastly, some of the communication tasks used are very artificial, such
as mathematical or verbal tests (natural conversations have been used more often in the
literature since 2003 than in the past). However, and according to Caird et al. (2008), artificial
cognitive tasks and natural conversations have comparable effects on reaction times.
In conclusion, experimental research has shown that mobile phone use while driving
deteriorate the processing of road information, thus increasing the probability of not
perceiving, or of perceiving too late, an important element of the environment. Added to this
are longer response times when an event occurs and judgment which is sometimes harmed.
Research aimed at showing adaptive behavior is limited and the few results obtained are
sometimes divergent. Handling a mobile phone to dial a number, to read or write an SMS, or
to consult internet services has an even more negative effect on driving. The increase in
reaction times is greater and these tasks lead to a diversion of the gaze towards the inside of
the vehicle, which has a very negative impact on lateral control. Biomechanical interference
with holding the steering wheel, linked to the monopolization of a hand, also adds to
difficulties controlling the trajectory and shows that carrying out such tasks of a visualmanual nature while driving can be very dangerous.
BIBLIOGRAPHY
ALIBALI MW, HEATH DC, MYERS HJ. Effects of visibility between speaker and listener on gesture
production: some gestures are meant to be seen. Journal of Memory & Language 2001, 44: 169-188
ALM H, NILSSON L. The effects of a mobile mobile phone task on driver behaviour in a car
following situation. Accident Analysis and Prevention 1995, 27: 707-715
ANTTILA V, LUOMA J. Surrogate in-vehicle information systems and driver behaviour in an urban
environment: A field study on the effects of visual and cognitive load. Transportation Research Part FTraffic Psychology and Behaviour 2005, 8: 121-133
BEEDE KE, KASS SJ. Engrossed in conversation: the impact of cell phones on simulated driving
performance. Accid Anal Prev 2006, 38: 415-421
BRIEM V, HEDMAN LR. Behavioural effects on mobile mobile phone use during simulated driving.
Ergonomics 1995, 38: 1536-2562
BROWN ID, TICKNER AH, SIMMONDS DCV. Interference between concurrent tasks of driving and
telephoning. Journal of Applied Psychology 1969, 53: 419-424
BRUYAS MP, TAFFIN M. Is there any difference between conversing by phone and conversing with
a passenger while driving? First International Conference on Driver Distraction and Inattention, A57P, Gothenburg, Sweden, 28-29 September 2009, 11p
Collective Expert Report
- 44 -
13/12/2011
BRUYAS MP, CHAPON A, LELEKOV-BOISSARD T, LETISSERAND D, DURAZ M, AILLERIE I.
Évaluation de l’impact de communications vocales sur la conduite automobile. Recherche Transports et
Sécurité 2006, 91: 99-119
BRUYAS MP, BRUSQUE C, DEBAILLEUX S, DURAZ M, AILLERIE I. Does making a conversation
asynchronous reduce the negative impact of phone call on driving? Transportation Research Part FTraffic Psychology and Behaviour 2009, 12: 12-20
BURNS PC, PARKES A, BURTON S, SMITH RK, BURCH D. How dangerous is driving with a mobile
phone? Benchmarking the impairment to alcohol. TRL Report, 547, Crowthorne, United Kingdom,
2002
CAIRD JK, WILLNESS CR, STEEL P, SCIALFA C. A meta-analysis of the effects of cell phones on
driver performance. Accid Anal Prev 2008, 40: 1282-1293
CHARLTON SG. Driving while conversing: cell phones that distract and passengers who react. Accid
Anal Prev 2009, 41: 160-173
CONSIGLIO W, DRISCOLL P, WITTE M, BERG WP. Effect of cellular mobile phone conversations
and other potential interference on reaction time in a braking response. Accid Anal Prev 2003, 35: 495500
COOPER JM, STRAYER DL. Effects of simulator practice and real-world experience on cell-phonerelated driver distraction. Hum Factors 2008, 50: 893-902
COOPER JM, VLADISAVLJEVIC I, MEDEIROS-WARD N, MARTIN PT, STRAYER DL. An
investigation of driver distraction near the tipping point of traffic flow stability. Hum Factors 2009, 51:
261-268
COOPER PJ, ZHENG Y, RICHARD C, VAVRIK J, HEINRICHS B, et al. The impact of hands-free
message reception/response on driving task performance. Accid Anal Prev 2003, 35: 23-35
CRUNDALL D, BAINS M, CHAPMAN P, UNDERWOOD G. Regulating conversation during driving:
a problem for mobile mobile phones? Transportation Research Part F-Traffic Psychology and Behaviour
2005, 8: 197-211
DREWS FA, PASUPATHI M, STRAYER DL. Passenger and cell phone conversations in simulated
driving. J Exp Psychol Appl 2008, 14: 392-400
DREWS FA, YAZDANI H, GODFREY CN, COOPER JM, STRAYER DL. Text messaging during
simulated driving. Human Factors 2009, 51: 762-770
ENDSLEY MR. Towards a theory of situation awareness in dynamic systems. Human Factors 1995, 37:
32-64
ENGSTRÖM JA, JOHANSSON EJ, ÖSTLUND J. Effects of visual and cognitive load in real and
simulated motorway driving. Transportation Research: Part F 2005, 8: 97-120
FAIRCLOUGH SH, ASHBY MC, ROOS T, PARKES AM. Effects of handsfree mobile phone use on
driving behavior. Proceedings of the isata symposium, Florence, Italy, 1991
GREEN M. “How long does it take to stop?” Methodological analysis of driver perception-brake
times. Transportation Human Factors 2000, 2: 195-216
GUGERTY L, RAKAUSKAS M, BROOKS J. Effects of remote and in-person verbal interactions on
verbalization rates and attention to dynamic spatial scenes. Accid Anal Prev 2004, 36: 1029-1043
HAIGNEY DE, TAYLOR RG, WESTERMAN SJ. Concurrent mobile (cellular) phone use and driving
performance: task demand characteristics and compensatory processes. Transportation Research Part F
2000, 3: 113-121
HANCOCK PA, LESCH M, SIMMONS L. The distraction effects of phone use during a crucial
driving maneuver. Accid Anal Prev 2003, 35: 501-514
HARBLUK JL, NOY YI, TRBOVICH PL, EIZENMAN M. An on-road assessment of cognitive
distraction: impacts on drivers’ visual behavior and braking performance. Accid Anal Prev 2007, 39:
372-379
HENDRICK JL, SWITZER JR. Hands-free versus hand-held cell phone conversation on a braking
response by young drivers. Percept Mot Skills 2007, 105: 514-522
Collective Expert Report
- 45 -
13/12/2011
HORBERRY T, ANDERSON J, REGAN MA, TRIGGS TJ, BROWN J. Driver distraction: the effects of
concurrent in-vehicle tasks, road environment complexity and age on driving performance. Accid Anal
Prev 2006, 38: 185-191
HORREY WJ, WICKENS CD. Examining the impact of cell phone conversations on driving using
meta-analytic techniques. Human factors 2006, 48: 196-205
HOSKING SG, YOUNG KL, REGAN MA. The effects of text messaging on young drivers. Human
Factors 2009, 51: 582-592
HUNTON J, ROSE JM. Cellular mobile phones and driving performance: The effects of attentional
demands on motor vehicle crash risk. Risk Analysis 2005, 25: 855-866
JAMSON AH, MERAT N. Surrogate in-vehicle information systems and driver behaviour: Effects of
visual and cognitive load in simulated rural driving. Transportation Research Part F-Traffic Psychology
and Behaviour 2005, 8: 79-96
JENNESS JW, LATTANZIO RJ, O’TOOLE M, TAYLOR N, PAX C. Effects of manual versus voiceactivated dialing during simulated driving. Percept Mot Skills 2002, 94: 363-379
KUNAR MA, CARTER R, COHEN M, HOROWITZ TS. Mobile phone conversation impairs sustained
visual attention via a central bottleneck. Psychon Bull Rev 2008, 15: 1135-1140
LABERGE J, SCIALFA C, WHITE C, CAIRD J. Effects of passenger and cellular phone conversations
on driver distraction. Driver and Vehicle Simulation, Human Performance, and Information Systems
for Highways; Railroad Safety and Visualization in Transportation 2004, 109-116
LAMBLE D, KAURANEN T, LAAKSO M, SUMMALA H. Cognitive load and detection thresholds in
car following situations: safety implications for using mobile (cellular) mobile phones while driving.
Accid Anal Prev 1999, 31: 617-623
LANSDOWN TC, BROOK-CARTER N, KERSLOOT T. Distraction from multiple in-vehicle
secondary tasks: vehicle performance and mental workload implications. Ergonomics 2004, 47: 91-104
MCCARLEY JS, VAIS MJ, PRINGLE H, KRAMER AF, IRWIN DE, STRAYER DL. Conversation
disrupts change detection in complex traffic scenes. Hum Factors 2004, 46: 424-436
NUNES LM, RECARTE MA. Cognitive demands of hands-freephone conversation while driving.
Transportation Research Part F: Traffic Psychology and Behaviour 2002, 5: 133-144
PACHIAUDI G. Les risques de l’utilisation du téléphone mobile en conduisant. Synthesis N° 39,
INRETS Collections, 2001, 62p
PATTEN CJD, KIRCHER A, OESTLUND J, NILSSON L. Using mobile mobile phones: cognitive
workload and attention resources allocation. Accid Anal Prev 2004, 36: 341-350
PEREIRA M. In-vehicle information system-related multiple task performance and driver behaviour:
comparison between different age groups. Ergonomics Thesis, Technological University of Lisbon,
Faculty of Human Motricity, 2009, 319p
PEREIRA M, BRUYAS MP, SIMÕES A. Are elderly drivers more at risk when interacting with more
than one in-vehicle system simultaneously? Le Travail Humain 2010, 73: 53-73
RAKAUSKAS ME, GUGERTY LJ, WARD NJ. Effects of naturalistic cell phone conversations on
driving performance. J Safety Res 2004, 35: 453-464
RANNEY TA, HARBLUK JL, NOY YI. Effects of voice technology on test track driving performance:
implications for driver distraction. Hum Factors 2005, 47: 439-454
RECARTE MA, NUNES LM. Effects of verbal and spatial–imagery tasks on eye fixations while
driving. Journal of Experimental Psychology: Applied, 2000, 6: 31-43
RECARTE MA, NUNES LM. Mental load and loss of control over speed in real driving. Towards a
theory of attentional speed control. Transportation Research Part F: Traffic Psychology and Behaviour
2002, 5: 111-122
RECARTE MA, NUNES LM. Mental workload while driving: effects on visual search, discrimination,
and decision making. J Exp Psychol Appl 2003, 9: 119-137
ROSENBLOOM T. Driving performance while using cell phones: an observational study. J Safety Res
2006, 37: 207-212
Collective Expert Report
- 46 -
13/12/2011
SALVUCCI DD, MACUGA KL, GRAY W, SCHUNN C. Predicting the effects of cellular-phone dialing
on driver performance. Cognitive Systems Research 2002, 3: 95-102
STRAYER DL, JOHNSTON WA. Driven to distraction: dual-Task studies of simulated driving and
conversing on a cellular mobile phone. Psychol Sci 2001, 12: 462-466
STRAYER DL, DREWS FA. Multitasking in the automobile. In: Attention: From theory to practice.
KRAMER AF, WIEGMANN DA, KIRLIK A (eds). Oxford University Press, New York, 2007a: 121-133
STRAYER DL, DREWS FA. Cell-phone-induced driver distraction. Current Directions in Psychological
Science 2007b, 16: 128-131
STRAYER DL, DREWS FA, JOHNSTON WA. Cell phone-induced failures of visual attention during
simulated driving. J Exp Psychol Appl 2003, 9: 23-32
STRAYER DL, DREWS FA, CROUCH DJ. A comparison of the cell phone driver and the drunk
driver. Hum Factors 2006, 48: 381-391
TÖRNROS JE, BOLLING AK. Mobile phone use-effects of handheld and handsfree phones on driving
performance. Accid Anal Prev 2005, 37: 902-909
TÖRNROS JE, BOLLING AK. Mobile phone use--Effects of conversation on mental workload and
driving speed in rural and urban environments. Transportation Research Part F: Traffic Psychology and
Behaviour 2006, 9: 298-306
TSIMHONI O, SMITH D, GREEN P. Address entry while driving: speech recognition versus a touchscreen keyboard. Hum Factors 2004, 46: 600-610
VICTOR TW, HARBLUK JL, ENGSTRÖM JA. Sensitivity of eye-movement measures to in-vehicle task
difficulty. Transportation Research: Part F 2005, 8: 167-190
Collective Expert Report
- 47 -
13/12/2011
4
Prevalence of mobile phone use at the wheel and
accidents
In order to estimate and understand the attributable risk of traffic accidents due to mobile
mobile phone use, it is important to know the frequency of this use in the general
population, during automobile driving as well as new uses, and obtain accident prevalence
data 5 .
Use of mobile mobile phones and other telecommunication systems
Trends in mobile mobile phone use in France
As noted in the expert report by AFSSET 6 (radiofrequencies working group, 2009); "the
mobile mobile phone is marked by massive, rapid and worldwide distribution". Few new
technologies have seen such deployment. The first mobile phones that were portable or
installed in cars (e.g. PBX) using analog technologies were first developed in the 1980s. The
mobile mobile phone was really developed during the 1990s with digital technologies in
GSM frequencies (firstly in the range of 900 MHz, then in the range of 1,800 MHz) and
further developed in the early 2000s in the UMTS range (still known as 'third generation', in
2,100 MHz).
Mobile mobile phone distribution was slightly slower in France than in numerous other
countries (e.g. Australia, Scandinavian countries, etc.). In the early 1980s, the first generation
of mobile mobile phones based on analog technology became widespread in Scandinavian
countries, the U.S.A. and Canada, but had very little presence in France. From 1991, the
GSM system was being marketed in Finland and Denmark. The first SIM cards 7 for the GSM
network appeared in France in 1992 and networks were established from 1994 onwards,
firstly in Paris and then in the largest cities, before extending to almost all of the national
territory. In 2009, 97.7% of the territory was covered, corresponding to 99.8% of the French
population (Gest, 2009). As shown in figure 4.1, real development in France began in 1997
with strong growth until 2001 (Idate Consulting and Research, 2009). The increase in the
number of users has continued at a slightly less sustained pace.
In 2008, 79% of French people were equipped with a mobile mobile phone. In June 2009,
ARCEP, the French Telecommunications and Posts Regulator, put forward the figure of
58.9 million subscribers to mobile telephony in France.
The rate of mobile mobile phone ownership varies according to age group, and decreases
with age: 97% of the 18-24 year age group, which represents the large majority of new
5
Prevalence is the frequency of an observed phenomenon in a given population at a precise moment (point prevalence) or
during the course of a period of time (usually annual: annual prevalence).
6
French agency for environmental health and work safety
7
The SIM (Subscriber Identity Module) card is a chip enabling the storage of specific information by the user of a mobile
network.
Collective Expert Report
- 48 -
13/12/2011
drivers, 95% of 25-29 year olds, 91% of 30-39 year olds, 83% of 40-59 year olds and 54% of
those aged 60 years and over.
Figure 4.1: Changes in the number of SIM cards in France (in millions) (from Idate Consulting and
Research, 2009, ARCEP data)
Comparison with other European countries
Although the French took longer than many of their European neighbors to embrace the
mobile mobile phone, today they are among the most "devoted" users (figure 4.2).
Figure 4.2: Duration of monthly mobile mobile phone use in outgoing calls (voice) by inhabitant
in 2008 (in minutes) (from Idate Consulting and Research, 2009)
Taking account of outgoing and incoming calls, on average the French communicate orally
by mobile mobile phone for between three and five hours per month.
New uses for mobile mobile phones
Thanks to transmission rates that are much superior to previous standards (GSM: 2nd
generation), the arrival of so-called third generation cellular telephony enables a very large
number of applications of the non-vocal transmission of information. These include, for
example, data, images and videos which are directly accessible from a mobile mobile phone
or via the intermediary of a 3G stick through internet connections from a portable computer.
In fact, mobile mobile phone usage has changed considerably in recent years, as shown in
figure 4.3.
Collective Expert Report
- 49 -
13/12/2011
Figure 4.3: Rate of multimedia function use (mobile customers aged over 12 years in France) (from
Idate Consulting and Research, 2009)
One illustration of these changes is represented by SMS (short message service) text messages.
The number of SMS text messages exchanged in France more than doubled between 2006
and 2008: 15,050 million SMS text messages had been exchanged in 2006 (1,250 million per
month); this number stood at 19,236 million in 2007, and at 34,396 million in 2008 (2,900
million per month) (ARCEP 2010).
All of these most recent applications are (or will be) equally available to vehicle drivers who
use a mobile mobile phone, as witnessed by the technical developments made available to
car drivers (and passengers) by mobile telephony operators and automobile manufacturers.
It is therefore probable that in the coming years usage will also diversify for the vehicle
driver. With oral communication becoming a more secondary element, the specific
constraints linked to these new uses will change the settings in terms of accidental risk.
Prevalence of mobile mobile phone use while driving
In order to estimate the proportion of traffic accidents due to mobile mobile phone use while
driving (risk of road accidents attributable to mobile mobile phones), prevalence data
regarding this use are needed, and the conditions of this. Various approaches are available
for trying to define this prevalence.
Methods for evaluating the prevalence of mobile mobile phone use
One of the most common methods consists of observing traffic at strategic road points. This
often involves intersections that oblige drivers to slow down and thus facilitate observation.
During these counting campaigns, the investigator notes the use or non-use of a mobile
phone by each vehicle driver passing in front of him/her. This is a point prevalence
evaluation 8 of hand-held mobile phone use only. It is much more difficult to accurately
determine the use of a "hands-free kit" from outside the car. These studies are very imprecise
in terms of characterization of the populations studied.
8
Point prevalence measures the rate of mobile mobile phone use among drivers traveling at a given moment.
Collective Expert Report
- 50 -
13/12/2011
In order to take into account not only hand-held mobile phones but also mobile phone use
via a hands-free kit, the Transport Research Laboratory (United Kingdom) has carried out
observation by detecting the radiofrequencies emitted by vehicles passing investigators
using a system handled by a second investigator.
Another approach consists of questionnaire based investigations into modes of use among
randomly selected representatives of the driving population, such as general surveys or
specific surveys on mobile mobile phones. These investigations focus especially on mobility
or road safety. They therefore seek to find out the percentage of subjects using mobile mobile
phones while driving. This type of investigation allows a much longer list to be drawn up of
all types of mobile phone use, or of other on-board devices. It is also possible to characterize
users and to have access to frequency of use and contexts of use reported by respondents.
Lastly, observations of driving in natural situations (known as "naturalistic driving studies")
consist of equipping the vehicles of a (necessarily) limited number of drivers with various
observation and sensor systems to enable the observation and recording of driver and
vehicle behavior on free trajectories, without the bias of self-declaration. Data gathered in
this way essentially allows the characteristics and situations of use to be located but does not
enable the calculation of prevalence rates, as this data is not representative of the general
driving population.
Prevalence rate of mobile phone use while driving
Prevalence rates of mobile phone use at the wheel have been collected in table 4.I. Three
types of prevalence are distinguishable: point prevalence, prevalence of use on a trajectory,
and finally prevalence of habitual use.
Point prevalence obtained by observation investigations
Two American studies carried out in the same conditions but with a four year interval (Eby
and Vivoda, 2003; Eby et al., 2006) show a doubling of the prevalence rate of hand-held
mobile phone use (2.7% and 5.8% respectively). The NHTSA study carried out in 2006
confirmed a prevalence of around 5%, which was slightly higher for female drivers (6%) than
male drivers (4%) (Glassbrenner and Jianqiang Ye, 2007).
In 2008, the American road safety administration provided a point prevalence rate for mobile
phone use by drivers carrying passengers of 6% (NHTSA, 2008).
This prevalence can be higher among young people: a study in North Carolina and South
Carolina (Foss et al., 2009) gave a prevalence rate of 11% to 13% among 16-17 year olds in
2007 (observation carried out in the "High Schools" of these two states).
In the Florence region in Italy, Lorini et al. (2006) calculated an average prevalence rate of
1.8% for hand-held mobile phones among 9,387 vehicle drivers observed in four parts of the
area. Higher prevalence rates were reported for drivers who were not wearing a seat belt
(3%) and when there were no passengers (2.1%).
In the United Kingdom, point prevalence was measured at 1.2% for hand-held mobile
phones and at 1.9% for hands-free mobile phones (Hill, 2005).
The extremely high point prevalence (34.7%) observed in Iran in 2007 (Mohammadi, 2009)
should be noted.
Vivoda et al. (2008) investigated night driving: the same prevalence was observed night and
day (5.8 ± 0.6%). However, mobile phone use while driving at night is more frequent among
young drivers and women: the highest rate was observed for women aged between 16 and
29 years (11.9% compared to 7.5% for men of the same age).
Collective Expert Report
- 51 -
13/12/2011
French studies
Using information collected during a questionnaire-based survey (frequency of use and
distance of daily journeys) and obtained information (average call length), the French
National Interministerial Observatory for Road Safety (ONISR) estimated that the point
prevalence of mobile phone use (hand-held or hands-free) in France was approximately 2.4%
(Chapelon, 2006).
A close prevalence for hand-held mobile phones (2.3%) was found through
counting/observing traffic carried out by ONISR (2009) on four road types (urban highways,
intercity highways, main roads or secondary roads in the open countryside, agglomerations):
1.8% for mobile phones held in the hand and to the ear, and 0.5% for mobile phones held in
the hand but not to the ear.
These figures will be used in the chapter dealing with epidemiological approaches to the risk
of accidents linked to mobile phone use at the wheel in order to calculate the proportion of
road accidents attributable to mobile mobile phones in France.
Generally speaking, it can be considered that these point prevalence rates are certainly
under-estimated, as most of the time these refer to a visual evaluation (hand-held mobile
phones, which does not take account of the use of hands-free kits).
Collective Expert Report
- 52 -
13/12/2011
Table 4.I: Prevalence rates of mobile phone use while driving according to studies
References/Countries
Mode of observation
Year
Place
Prevalence rate
Comments
Eby and Vivoda, 2003
U.S.A: Michigan
Observation at
strategic intersections
2001
168 places stratified
and drawn randomly
2.7% ± 0.3 of
motorists
Eby et al., 2006
U.S.A: Michigan
Observation at
strategic intersections
2005
168 places stratified
and drawn randomly
5.8% of motorists
Same methodology as the
previous study: Doubling of
rates in 4 years
Bedford et al., 2005
Ireland
Observation at
strategic points
2005
4 intersections
3.6% [2.6-4.9] of
motorists:
hand-held mobile
phone in rural areas
1,075 vehicles per day
Hill, 2005
United Kingdom
Observation at
strategic points
2005
38 sites
1.2%: hand-held
mobile phone
1.9%: hands-free
mobile phone
Visual observation combined
with field detection in
corresponding radiofrequency
bands emitted by passing cars
Lorini et al., 2006
Italy
Observation at
strategic points
2006
4 observation points
in the Florence region
1.8% of motorists
hand-held mobile
phone
Vivoda et al., 2008
U.S.A.
Observation at
strategic points
2006
113 randomly drawn
observation points
5.8% (± 0.6)
(11.9% among young
women)
Night driving prevalence rate
Glassbrenner and Jianqiang
Ye, 2007
U.S.A.
Observation at
strategic points
2006
1,200 observed sites
5% hand-held mobile
phone (4% men; 6%
women)
0.6% for observable
hands-free mobile
phone kits
NOPUS study on 43,000
vehicles
Foss et al., 2009
U.S.A.
Observation at
strategic points
around schools
2007
25 schools in North
Carolina
5 schools in South
Carolina
11% use in North
Carolina
13 % in South
Carolina
Study of young people aged
16-17 years
Indicator measured: Point
prevalence
Collective Expert Report
- 53 -
13/12/2011
References/Countries
Mode of observation
Year
Place
Prevalence rate
Mohammadi, 2009
Iran
Observation at
strategic points
2007
4 intersections on 2
major roads
Mobile phone held at
the wheel by
drivers=34.7%
NHTSA, 2008
U.S.A.
Observation at
strategic points
2007
McCartt et al., 2010
U.S.A.
Observation at
strategic points
2009
8 intersections in each
of the three areas
6%
Observation by traffic police
Mobile phone held at
the wheel by drivers
in the District of
Columbia: 4.2%
District of Columbia
Maryland suburbs of
DC: 5.2%
Virginia suburbs of
DC: 8.5%
ONISR, 2008
France
Comments
Observation at
strategic points
2007
15,335 observed
drivers
1.9% mobile phones
held in the hand and
to the ear
0.5% mobile phones
held in the hand but
not to the ear (SMS
text messages?
dialing? etc.)
"Naturalistic driving
studies"
2002
70 equipped subjects
34.3% of subjects
used their mobile
phone, or 3.8% of
their journey time
Investigation by
survey
2003
Drivers
32.8% of drivers
possessing a mobile
mobile phone say
Maryland
Virginia: legislation
implemented in 2004
Rate standardized on the
category network
Indicator measured:
Percentage of use on
journey length
Stutts et al., 2003
U.S.A.
Indicator measured:
Prevalence of use
Brusque and Alauzet, 2008
France
Collective Expert Report
- 54 -
13/12/2011
Investigation regarding
landline mobile phone users
(does not take account of
References/Countries
Mode of observation
Year
Place
Prevalence rate
Comments
they use the mobile
phone while driving
(or 20% of drivers)
subjects who only possess a
mobile mobile phone).
Laberge-Nadeau et al., 2003
Quebec
Cross-disciplinary
epidemiological
study
2003
Quebec insurance
company (SAAQ)
policyholders
38.6% of men and
22% of women use a
mobile mobile phone
when driving
36,078 participants out of
175,000 approached (response
rate 20.6%)
Charbotel et al., 2007
France
Case-control
epidemiological
study
2006
Drivers
36% of questioned
subjects said that they
used their mobile
mobile phone while
driving every day
Control subjects from a casecontrol study
Chapelon and Sibbi, 2007
France
Investigation by
survey
2006
Drivers
44% of drivers use
their mobile phone
when driving (10%
use it often or very
often)
From the data collected, point
prevalence is estimated at 2.4%
McEvoy et al., 2006
Australia
Cross-disciplinary
epidemiological
study
2003
Driving license
holders
57.3% of holders have
used a mobile mobile
phone when driving
12.4% have sent SMS
text messages when
driving
57% have previously made
calls when driving
12% have previously sent SMS
text messages when driving
Collective Expert Report
- 55 -
13/12/2011
Survey-based investigations
In Australia, McEvoy et al. (2006) carried out a study of practices among 1,347 subjects
holding a driving license: 57.3% of driving license holders have previously used a mobile
mobile phone and 12.4% have previously written SMS text messages when in an automobile
driving situation.
In the U.S.A., a study by Dong Chul (2004) shows that among the 1,185 learner drivers in
their sample, 86% of these used, at least occasionally, their mobile mobile phone when
driving.
In France, we have two studies at our disposal on the use of mobile mobile phones at the
wheel: one comes from a study carried out by LESCOT (INRETS) in 2003 (Brusque and
Alauzet, 2006) based on a sample of 1,973 subjects questioned by mobile phone; the other
comes from a survey conducted for ONISR in 2006.
In 2003, among 1,973 subjects questioned, 1,480 (819 men and 661 women) were vehicle
drivers, of whom 920 were also mobile mobile phone owners. Among the latter, 33%
reported that they had used the mobile phone while driving (40% of men and 23% of
women) (figure 4.4).
Figure 4.4: Distribution of drivers who are mobile mobile phone users according to the number of
daily calls made when driving (N= 920)
In 2006, out of the 1,000 people surveyed (IFOP survey conducted on behalf of the French
National Interministerial Observatory for Road Safety (ONISR)), 664 said that they were a
driver and the owner of a mobile mobile phone: 44% of the latter said they used their mobile
phone while driving:
•
for 20% of drivers, this usage was very rare;
•
for 14%, this usage was rare;
•
for 6%, this usage was frequent;
•
for 4%, this usage was very frequent: men, the Paris and South West regions and
high mileage drivers are over-represented in these last two groups.
This study also provided knowledge of the mode of mobile phone use when driving:
•
41% use a conventional hand-held mobile phone;
Collective Expert Report
- 56 -
13/12/2011
•
37% use earphones;
•
14% use their mobile phone's hands-free function;
•
7% use a hands-free device installed in the vehicle.
Furthermore, two as yet unpublished studies carried out in the Rhone département have
obtained rates of mobile mobile phone use while driving in two population types: the first is
a population of drivers who have been involved in accidents (ESPARR Cohort, personal
data). In 2004-2005, 34% of drivers who had been involved in accidents from the ESPARR
cohort said that they used a mobile mobile phone while driving (8% of drivers said they used
it more than 10% of the time while driving). The other study is a case-control study
comparing drivers who have been involved in accidents during work (case) with drivers
representing the population of drivers circulating (controls) in 2006 (Charbotel et al., 2007):
•
36% of control drivers said that they use their mobile mobile phone every day
while driving;
•
37% use it occasionally;
•
28% never use it.
In 2003 (Thulin and Gustafsson, Sweden, 2004), on average one SMS text message per week
was sent or received while driving (3 SMS text messages/week for under 25 year olds).
A survey requested by the French National Interministerial Observatory for Road Safety
which was carried out in 2008 shows that drivers admitting to telephoning while driving say
that on average they receive and read one SMS text message every 350 km, and send one
approximately every 670 km (ONISR, 2009).
Use of mobile mobile phones by users other than drivers of four-wheeled vehicles
There is practically no data concerning use by drivers of two-wheeled motorized vehicles or
bicycles.
An observational study in the Netherlands looked at cyclists (by Waard et al., 2010). The
authors observed 2,138 cyclists in three places:
•
2.2% used their mobile mobile phone (and held their handlebar with one hand);
•
0.6% sent an SMS text message;
•
7.7% listened to an MP3 player.
Concerning the proportion of users, only data from gray literature is currently available. A
study on cyclists in France showed that 13% of cyclists using a bicycle as a method of
transport and 26% of those who cycle for sport said that they sometimes or often use a
mobile mobile phone (Amoros et al., 2009). In the framework of the ESPARR cohort: 5% of
drivers of two-wheeled motorized vehicles who have been involved in an accident and
participated in the study said that they were occasional or infrequent users of mobile mobile
phones when driving, mainly via use of a hands-free kit.
Characterization of drivers using their mobile phone while driving
Individual characteristics shared by users of mobile mobile phones while driving have been
highlighted in several studies (table 4.II).
Collective Expert Report
- 57 -
13/12/2011
Young people
The majority of studies have highlighted a high prevalence rate of mobile mobile phone use
among young people (Lagarde et al., 2004; Sullman and Baas, 2004; Bener et al., 2006;
Brusque and Alauzet, 2006; Glassbrenner and Jianqiang Ye, 2007; Taylor et al., 2007). In
particular, the sending and receiving of SMS text messages when driving mainly concerns
the age group of drivers under 35 years (Thulin and Gustafsson, 2004; Chapelon and Sibi,
2007).
Male drivers
Mobile mobile phone users are most frequently men (Brusque and Alauzet, 2006; Chapelon
and Sibi, 2007; Taylor et al., 2007; Farmer et al., 2010). However, with regards to night
driving, young women are more frequently noted using mobile mobile phones (Vivoda et al.
2008).
Road professionals
The population of road professionals is especially likely to use mobile mobile phones in the
sense that the road is their workplace. In a work context, it is more or less implicitly
acknowledged that a road professional must be in constant contact with their manager and
customers, as well as family members. In fact, as a method of organizing journeys, rounds
and deliveries, the mobile mobile phone is a tool which facilitates the organization of
professional tasks, or reduces the stress in situations of delay or problems on the road.
Conversely, due to the mobile phone, the worker on the road is under constant work
pressure and no longer benefits from moments of "uncoupling" that certain periods and
journey conditions might have generated in the past.
Several studies have considered the behavior of road professionals (Harris et al., 2003;
Taylor and Dorn, 2006) and have enabled the prevalence of mobile mobile phone use while
driving and certain characteristics of this behavior to be measured.
Thus, according to Troglauer et al. (2006), Danish heavy goods vehicle drivers are
characterized by the fact that 99% of them use a mobile mobile phone, and more than 40%
use a hand-held mobile phone (30% hands-free kits, 28% kit + hand-held mobile phone, 41%
hand-held mobile phone). Over 50% stop during a call in all circumstances, 50% never stop
when making a call themselves, 36% stop less than half the time, and 45% send SMS text
messages while driving. For 63% of these road professionals, mobile phone calls are of a
professional nature 90% of the time.
In an American "naturalistic driving" study (Hickman et al., 2010), for 2.1% of accident-free
driving observation time, heavy goods vehicle or bus drivers were involved in a mobile
mobile phone-related task (of which 0.8%were involved in a conversation using a hands-free
mobile phone and 1.1% in conversation using a hand-held mobile phone). This percentage
stood at 3.5% when the company the driver worked for had no "good practice" rule relating
to mobile mobile phones. However, it is difficult to generalize this result insofar as the
analyzed accident-free observation time periods are still particular times when something
happened that justified recording the parameters by on-board equipment.
In France, tallying conducted for ONISR (2008) gives a point prevalence rate of 3.4% for
drivers of light commercial vehicles; mobile mobile phone use being mainly implemented
during traveling on highways (urban and intercity) or in agglomerations. In terms of heavy
goods vehicle drivers, the same survey provided a prevalence rate of 2.6%, with use mainly
being implemented on urban and intercity routes (roads and highways), and almost never in
agglomerations.
Collective Expert Report
- 58 -
13/12/2011
Length of calls and distance covered
Length of communications (voice calls or SMS text messages) represents accident risk
exposure time linked to a driver's mobile mobile phone use. This is therefore essential
epidemiological data as it is closely linked to subjects' daily driving time. In a Swedish study
(Thulin and Gustafsson, 2004), it stood at 23 minutes per day among tractor-trailer drivers, at
12 minutes for medium-haul freight truck drivers, between 7-9 minutes for taxi drivers and 7
minutes for private individuals.
The daily length of mobile phone communication when driving was also researched among
Danish road professionals (Troglauer et al., 2006). It was:
•
less than 5 minutes/day for 16% of road professionals who used a mobile mobile
phone;
•
between 5 and 15 minutes/day for 47% of these;
•
between 16 and 30 minutes/day for 26% of these;
•
over 30 minutes/day for the 11% of heaviest users.
This study also showed that the daily length of communication varied according to age, sex,
journey length, and the number of stops during the journey.
According to Farmer et al. (2010), from a sample of 1,219 of subjects who had driven the
week before the investigation, time spent on the mobile phone when driving was on average
4 minutes per day, or 6.7% of daily journey time (which corresponded on average to 1.3 calls
per subject, the average length of these calls being 3.1 minutes per call). However, it should
be noted that the significant rate of refusal to participate in the investigation (78%) limits
interpretation of this information. The precision of these evaluations by questionnaire of time
spent at the wheel is debatable.
According to Brusque and Alauzet (2008), men mobile phone 5 times more for professional
reasons than for private reasons. Among women, driving more than 25,000 km per year
multiplies by 3 the risk of using a mobile mobile phone at the wheel compared to those who
drive less than 25,000 km per year.
The same observation of the relationship between mobile mobile phone use when driving
and annual mileage was also found by Pöysti et al. (2005) in Finland.
Overall, the results are therefore fairly consistent: men, young people and those who drive
the most, in particular for professional reasons, have higher rates of mobile mobile phone use
at the wheel. These factors are generally taken into account as balancing variables in studies
that compare the risk of accidents between users and non users.
Furthermore, some results suggest that high-risk driving behaviors could be higher among
mobile mobile phone users. However, the differences observed are too few to explain
differences in accident risk. We do note however that studies fail to conclude with certainty
on the latter point with regards to differential behavior between users and non-users.
Collective Expert Report
- 59 -
13/12/2011
Table 4.II: Characteristics of users of mobile mobile phones when driving in different studies
Reference/Country
Type of study
Period
Population
Sample size
Identified variables
McCartt et al., 2003
U.S.A.
Direct observation
2001-2002
Drivers
37,462 (NY)
21,315
(Connecticut)
Youth
4X4 vehicle
Lagarde et al., 2004
France
Investigation by selfadministered
questionnaires sent by mail
2001
Members of a
cohort of salaried
workers
13,852
Youth
Km covered/year
Alcohol consumption
Superior vehicle category
Negative attitudes with regards to
road safety rules
Less than 10 points on license
Sullman and Baas,
2004
New Zealand
Investigation by selfadministered
questionnaires distributed
at service stations
2002
Drivers
861
Youth
Inexperience
Higher usual speeds
Km covered/year
Bener et al., 2006
Quatar
Investigation by
questionnaires
administered by
investigators
2004-2005
Drivers involved in
a traffic accident
822
Youth
Inexperience
Profession
Illiteracy
Eby et al., 2006
U.S.A.
Direct observation
2005
Drivers
10,759
Slightly lower seat belt use
Troglauer et al.,
2006
Denmark
Investigation by selfadministered
questionnaires sent by mail
2003
Heavy goods
vehicle drivers
1,153
Youth
Time (max=11 a.m. - 5 p.m.)
Highway
Walker et al., 2006
Great Britain
Direct observation
2005
Drivers
41,126
Lower seat belt use
4X4 vehicle
Glassbrenner and
Jianqiang Ye, 2007
U.S.A.
Direct observation
2005
Drivers
43,000
Youth
Taylor et al., 2007
Australia
Direct observation
2006
Drivers
20,207
Youth
Sex (m>f)
Brusque and
Mobile phone investigation
2003
Mobile mobile
1,973
Sex (m>f)
Collective Expert Report
Page 60
13/12/2011
Alauzet, 2008
France
Vivoda et al., 2008
U.S.A.
Collective Expert Report
phone users
Direct observation
2008
Night drivers
Page 61
Youth
Frequency of use
Professional use
Km covered/year
7,076
Youth
Sex (m>f)
4X4 vehicle
Time (before 2 a.m.)
13/12/2011
Prevalence of the use of other "on-board equipment" while driving
Few studies have looked at on-board equipment other than mobile mobile phones that can
be a source of distraction. The most significant are studies by traffic police intervening in
road accidents (mainly in the U.S.A.) or observations on driving in natural situations.
The already dated study by Stutts et al. (2003) evaluated the percentage of driving time spent
handling systems (such as radio, cassettes, etc.) at 1.5% and time spent reading or writing at
the wheel at 1.8%.
In the French study by Charbotel et al. (2007), 95% of drivers said they used embedded
computing (occasionally or frequently), 15% a GPS system and 10% used a CB radio. In
addition, one driver in three declared that he might take notes while driving.
Prevalence of use of mobile mobile phones and other systems in accidents
in international literature
Data on the prevalence of mobile phone use in accidents in police reports or in
observations of driving in natural situations
Since 2002 the American police force has noted the presence of a mobile mobile phone as a
possible distracting agent responsible for an accident in a proportion of accidents ranging
from 0.1 per thousand to 25 per thousand (Violanti, 1997 and 1998). In Australia in 2002,
Lam (2002) estimated that a mobile mobile phone had been involved in 2.4 accidents per
1,000.
However, there are significant limits to these evaluations:
•
existing reports are often police reports, with no standardized recording method;
•
mobile mobile phones are only reported when there is no other obvious cause;
•
serious accidents due to mobile mobile phones are over-estimated as these
investigations are more thorough;
•
these studies are already old, while mobile mobile phone use has been in constant
growth since its implantation in the general population.
An American "naturalistic driving" study of "100 cars" gives a 3.6% frequency of use in
accident situations or "near-accidents" observed during the trial period (Klauer et al., 2006).
A study of heavy goods vehicle and bus drivers gives a prevalence of 0.5% for mobile mobile
phone use in an accident or near-accident (Hickman et al., 2010).
"Naturalistic driving" studies, although enabling causes of distraction to be organized into a
hierarchy, do not facilitate a good evaluation of prevalence of mobile phone use in accidents
for several reasons, including:
•
an accident is a rare event just as mobile mobile phone use is, and the observed
number of a combination of these events is therefore very low. Prevalence rates
are thus very imprecise;
•
the basic events serving as periods of comparison are not representative of all
accident-free driving;
•
the observed drivers are not representative of the general driving population.
Collective Expert Report
13/12/2011
Page 62
It would be interesting to conduct studies on the prevalence of mobile mobile phone use
during accidents in France, provided that the collection method was systematized,
standardized and validated by data collection from mobile phone operators.
Prevalence data in epidemiological studies
The difficulty encountered by epidemiologists on accessing data on actual exposure to
mobile mobile phones has led them to envisage diverse scenarios in order to evaluate
exposure at the time of an accident.
The first study in this field was conducted by Redelmeier in 1995 (Redelmeier et al., 1997)
and remains the benchmark study. The evaluation of the exposure of subjects involved in an
accident is retrieved from mobile phone companies: mobile phone calls by subjects taking
place in the 10 minutes preceding the presumed moment of the accident are taken into
account insofar as the exact time of the accident is unknown. Thus, 24% of drivers involved
in accidents (collisions without injuries) who were owners of mobile mobile phones used a
mobile mobile phone during this 10 minute period, corresponding to around 3.1% of drivers
involved in accidents.
In a study by McEvoy et al. (2006) among 1,347 subjects holding a driving license, 0.9%(±
0.3) were estimated to have had an accident when using a mobile mobile phone and 3.0% (±
0.6) had had to execute an emergency maneuver in order to avoid an accident when using a
mobile mobile phone.
McEvoy et al. (2005) conducted the same type of study as Redelmeier (Crossover study where
the subject involved in the accident is their own witness; see epidemiology chapter): 7% of
drivers involved in accidents (excluding serious accidents, i.e. death or severe head injury)
who were mobile mobile phone owners acknowledged having used their mobile phone in
the 10 minutes preceding the accident (whether hand-held or hands-free), which at the time
corresponded to 3.5% of those involved in accidents.
In another publication, which related to the same study but focused on general causes of
distraction, McEvoy et al. (2007) indicated that 2% of drivers involved in an accident
(excluding serious accidents according to the same criteria) had reported using a mobile
mobile phone or the radio at the moment of the accident.
Young people have been the subject of slightly more precise studies but the results are
variable. For Dong-Chul (2004), 21% of young students (5 universities from two states in the
Midwest and from two Southern U.S. states) who had had an accident or a "near accident"
blamed a mobile phone conversation by the driver, while for Neyens and Boyle (2008) use of
a mobile mobile phone was blamed as a source of distraction for 0.4% of young drivers
involved in accidents aged 16-19 ans. For Braitman et al. (2008), it was blamed for 2% of
young drivers involved in accidents having gained their driving license less than eight
months before the accident. This difference can undoubtedly be explained by the fact that the
student population surveyed in the first study is indisputably not representative of the total
population of young people in the four states studied.
According to a study by Wilson et al. (2003), mobile mobile phone users are more often
responsible for an accident they are involved in; they are more often involved in rear-end
collisions (Sagberg, 2001; Wilson et al., 2003). Furthermore, they have no more fines for
careless driving than others. These same characteristics were highlighted in the study by
McEvoy et al. (2007), which also noted the frequency of accidents with no other party
involved ("one party" accidents).
Collective Expert Report
13/12/2011
Page 63
In conclusion, the methods of diverse published studies are variable and do not produce the
same information. The very rapid changes in mobile mobile phone use partly explain the
significant variations in evaluations, which are often old and certainly underestimate current
use of mobile mobile phones while driving. Only the most recent data is relevant to
evaluating the current risk attributable to mobile mobile phones and other on-board
materials. Uses themselves (3G technology, multimedia) currently modify the settings in
terms of potential risk.
Thus, at any time, 5% to 6% of drivers have a mobile phone in their hand, according to one of
the most recent studies (2008) (night or day). Between 10% and over 40% of drivers use the
mobile phone at the wheel at least once a day.
The heaviest users of the mobile phone while driving have an average length of
communication of 10 minutes per day.
It seems that accidents linked to mobile mobile phone use represent between 1% of accidents
(police reports) and 4% (epidemiological observation studies), but significant uncertainties
(mode of use, changes in use, observation difficulties, etc.) on these studies oblige cautious
interpretation of this data.
The accidents most frequently associated with mobile mobile phone use while driving are
rear-end collisions or collisions with a stationary obstacle.
BIBLIOGRAPHY
AMOROS E, SUPERNANT K, GUÉRIN AC, CHIRON M. Cyclistes victimes d’accidents : partie 3
enquête sur l’utilisation du casque et des équipements de visibilité. UMRESTTE Report N°0913, Oct.
2009
ARCEP. Rapport public d’activité de l’ARCEP 2009. 2010, 116-117
BEDFORD D, O’FARRELL A, DOWNEY J, McKOWN F. The use of hand held mobile phones by
drivers. Irish Med J 2005, 98: 248
BENER A, LAJUNEN T, ÖZKAN T, HAIGNEY D. The effect of mobile phone use on driving style and
driving skills. I J Crash 2006, 11: 459-465
BRAITMAN KE, KIRLEY BB, McCARTT AT, CHAUDHARY NK. Crashes of novice teenage drivers:
characteristics and contributing factors. J Safety Research 2008, 39: 47-54
BRUSQUE C, ALAUZET A. L’utilisation du téléphone mobile au volant en France : entre déni du
risque et autorégulation du comportement. Rech Transport Sécurité 2006, 91: 75-97
BRUSQUE C, ALAUZET A. Analysis of the individual factors affecting mobile phone use while
driving in France: socio-demographic characteristics, car and phone use in professional and private
contexts. Accid Anal Prev 2008, 40: 35-44
CHAPELON J, SIBBI P. Le téléphone portable au volant. Observatoire national interministériel de
sécurité routière, Report 28 March 2007
CHARBOTEL B, FORT E, RENAUX C, DAVEZIES P, CHIRON M, et al. Facteurs de risque des
accidents de la route liés au travail : Enquête cas-témoins à partir du registre du Rhône des victimes
d’accidents de la circulation. UMRESTTE Report, June 2007
DE WAARD D, SCHEPERS P, ORMEL W, BROOKHUIS K. Mobile phone use while cycling:
incidence and effects on behaviour and safety. Ergonomics 2010, 53: 30-42
DONG-CHUL S. The impact of in-vehicle cell-phone use on accidents or near-accidents among college
students. J Am College Health 2004, 53: 101-107
EBY DW, VIVODA JM. Driver hand-held mobile phone use and safety belt use. Accid Anal Prev 2003,
35: 893-895
Collective Expert Report
13/12/2011
Page 64
EBY DW, VIVODA JM, ST LOUIS RM. Driver hand-held cellular phone use: a four-year analysis. J
Safety Res 2006, 37: 261-265
FARMER CM, BRAITMAN KA , LUND AK. Cell phone use while driving and attributable crash risk.
Traffic Inj Prev 2010, 11: 466-470
FOSS RD, GOODWIN AH, MCCARTT AT, HELLINGA LA. Short-term effects of a teenage driver cell
phone restriction. Accid Anal Prev 2009, 41: 419-424
GEST A. Les incidences éventuelles sur la santé de la téléphonie mobile. Les rapports de l’OPECST.
Office Parlementaire d’évaluation des choix scientifiques et technologiques Paris, 2009
GLASSBRENNER D, JIANQIANG YE T. Driver Cell Phone Use in 2006-Overall results. Washington,
NHTSA’s National Center for Statistics and Analysis, 2007
RADIOFREQUENCIES WORKING GROUP. Specialist expert committee linked to evaluation of risks
linked to physical agents, new technologies and major developments. "Les Radiofréquences : Mise à
jour de l’expertise relative aux radiofréquences". Physiques Es-A, AFSSET, Paris, 2009, 465p
HARRIS G, MAYHO G, PAGE L. Occupational health issues affecting the pharmaceutical sales force.
Occup Med 2003, 53: 378-383
HILL JP. A survey of mobile phone used by drivers. TRL Report N° TRL635, April 2005
HICKMAN JS, HANOWSKI RJ, BOCANEGRA J. Distraction in commercial trucks and buses:
assessing prevalence and risk in conjunction with crashes and near-crashes. US department of
Transportation, Federal Motor Carrier Safety Administration, Report, Sept. 2010
IDATE CONSULTING AND RESEARCH. Observatoire économique de la téléphonie mobile : faits et
chiffres 2008. La revue d’expertise de l’Association Française des Opérateurs Mobiles. Paris, AFOM,
2009
KLAUER SG, DINGUS TA, NEALE VL, SUDWEEKS JD, RAMSEY DJ. The impact of Driver
Inattention on near/crash risk: an analysis using the 100-car Naturalistic Study Data. Report N° DOT
HS 810 594, National Highway Traffic Safety Administration, Washington 2006: 226
LABERGE-NADEAU C, MAAG U, BELLAVANCE F, LAPIERRE SD, DESJARDINS D, et al. Wireless
mobile phones and the risk of road crashes. Accid Anal Prev 2003, 35: 649-660
LAGARDE E, CHIRON M, LAFONT S. Traffic ticket fixing and driving behaviours in a large French
working population. J Epidemiol Community Health 2004, 58: 562-568
LAM LT. Distractions and the risk of car crash injury: the effect of drivers’ age. J Safety Res 2002, 33:
411-419
LORINI C, BONACCORSI G, MERSI A, BARONCINI O, CIAMPI G, et al. Mobile phone use while
driving in Florence health district area. Ann Ig 2006, 18: 349-356
McCARTT AT, BRAVER ER, GEARY LL. Drivers’ use of hand-held cell phones before and after New
York State’s cell phone law. Prev Med 2003, 36: 629-635
McCARTT AT, HELLINGA LA, STTROUSE LM, FARMER CM. Long-term effects of handheld cell
phone laws on driver handheld cell phone use. Traffic Inj Prev 2010, 11: 133-141
McEVOY SP, STEVENSON MR, MCCARTT AT, WOODWARD M, HAWORTH C, et al. Role of
mobile phones in motor vehicle crashes resulting in hospital attendance: a case-crossover study. BMJ
2005, 331: 428
McEVOY SP, STEVENSON MR, WOODWARD M. Phone use and crashes while driving: a
representative survey of drivers in two Australian states. Med J Austral 2006, 185: 630-634
McEVOY SP, STEVENSON MR, WOODWARD M. The prevalence of, and factors associated with,
serious crashes involving a distracting activity. Accid Anal Prev 2007, 39: 475-482
MOHAMMADI G. Mobile phone and seat belt usage and its impact on road accident fatalities and
injuries in southeast Iran. Intern J Crashworthiness 2009, 14: 309-314
Collective Expert Report
13/12/2011
Page 65
NEYENS DM, BOYLE LN. The influence of driver distraction on the severity of injuries sustained by
teenage drivers and their passengers. Accid Anal Prev 2008, 40: 254-259
NHTSA. Traffic safety facts, research note: driver electronic device use in 2007. Publication N° DOT
HS 810 963. National Highway Traffic Safety Administration.
Washington DC. 2008.
http://www-nrd.nhtsa.dot. Gov/Pubs/810963.PDF
OBSERVATOIRE NATIONAL INTERMINISTÉRIEL DE LA SÉCURITÉ ROUTIÈRE (ONISR). La
sécurité routière en France : bilan de l’année 2007. La Documentation française, Paris, 2008
OBSERVATOIRE NATIONAL INTERMINISTÉRIEL DE LA SÉCURITÉ ROUTIÈRE (ONISR). La
sécurité routière en France : bilan de l’année 2008. La Documentation française, Paris, 2009 : 108-110
PÖYSTI L, RAJALIN S, SUMMALA H. Factors influencing the use of cellular (mobile) phone during
driving and hazards while using it. Accid Anal Prev 2005, 37: 47-51
REDELMEIER DA, TIBSHIRANI RJ. Association between cellular-mobile phone calls and motor
vehicle collisions. N Engl J Med 1997, 336: 453-458
SAGBERG F. Accident risk of car drivers during mobile mobile phone use. Int J Vehicle Design 2001,
26: 57-69
STUTTS J, FEAGANES J, RODGMAN E, HAMLETT C, REINFURT D, et al. The causes and
consequences of distraction in everyday driving. Annu Proc Assoc Adv Automot Med 2003, 47: 235-251
SULLMAN M, BAAS P. Mobile phone use amongst New Zealand Drivers. Transportation Research
Part F 2004, 7: 95-105
TAYLOR AH, DORN L. Stress, fatigue, health and risk of road traffic accidents among professional
drivers: the contributions of physical inactivity. Annu Review Pub Health, 2006, 27: 371-391
TAYLOR DM, MACBEAN CE, DAS A, MOHD ROSLI R. Handheld mobile mobile phone use among
Melbourne drivers. Med J Aust 2007, 187: 432-434
THULIN H, GUSTAFSSON S. Mobile phone use while driving: conclusions from four investigations.
Swedish National Road and Transport Research Institute. VTI Rapport 490A-2004
TROGLAUER T, HELS T, CHRISTENS PF. Extent and variations in mobile phone use among drivers
of heavy vehicles in Denmark. Accid Anal Prev 2006, 38: 105-111
VIOLANTI JM. Cellular phones and traffic accidents. Pub Health 1997, 111: 423-428
VIOLANTI JM. Cellular phones and fatal traffic collisions. Acc Anal Prev 1998, 30: 519-524
VIVODA JM, EBY DW, ST LOUIS RM, KOSTYNIUK LP. Cellular phone use while driving at night.
Traffic Inj Prev 2008, 9: 37-41
WALKER L, WILLIAMS J, JAMROZIK K. Unsafe driving behaviour and four wheel drive vehicles:
observational study. Br Med J 2006, 333: 71-73
WILSON J, FANG M, WIGGINS S. Collision and violation involvement of drivers who use cellular
mobile phones. Traffic Inj Prev 2003, 4: 45-52
Collective Expert Report
13/12/2011
Page 66
5
Epidemiological approach of the risk of an accident
linked to telephoning while driving
Does telephoning while driving modify the risk of having an accident, and to what degree? If
there is an increase in the risk, does it depend on the system used (whether or not handsfree)? Out of all accidents, what proportion can be attributed to "telephoning while driving"?
According to common practice in epidemiology, the response to the first question entails
calculating the relative risk (RR) estimated by dividing the risk for a driver to have an
accident while telephoning by the risk of having an accident without telephoning.
RR =
Risk of an accident while telephoning
Risk of an accident without telephoning
The evaluation of this RR ratio supposes knowledge, during a given period of observation, of
the periods during which each driver in the sample observed was driving using a telephone
or not. This also supposes knowledge of any accidents that occurred during the same period.
The rather low number of epidemiological studies available in international literature and
which are pertinent to the subject can be explained by the difficulty in obtaining this
information on samples that are large enough. Emphasis must also be given to an additional
difficulty related to the intermittence in exposure to driving and to telephone use. Contrary
to many exposures examined in public health, the effect of using a telephone is transitory
(the disturbance effect on driving is assumed to cease as soon as or very shortly after
stopping the use of the telephone). This requires having precise knowledge of the various
periods of exposure and of the exact moment of the accident. In addition, it is necessary RR
estimates should reflect the sole effect of telephone use on the road crash risk, which can be
obtained by choosing a type of study that is adapted, and by making adjustment for the
other factors that can simultaneously affect the occurrence of an accident and on telephone
use. As RR cannot be always estimated directly, many studies (table 5.I) estimate the odds
ratio (OR) which is a good approximation in the case where the event of interest is "rare".
This is the case when we are interested in the occurrence of an accident, which is a rare event
for a driver.
Table 5.I: Approximation of the relative risk (RR) via the odds ratio
For example if in a case-control study, the cases are the accidents (noted as A+) and the controls are the nonaccidents (A-), and if we are interested whether they were telephoning (T+) or not (T-), the RR, equal to
P(A+/T+)/P(A+/T-), no longer has any meaning as it depends on the number of cases and controls included in
the study (with P(A+/T+) meaning the probability of being in an accident among the telephoning drivers).
Another measure of association, the odds ratio (OR), equal to the ratio of the P(A+/T+)/P(A-/T+) and P(A+/T)/P(A-/T-) ratios, and of which it can be shown that it is also equal to the ratio of P(T+/A+)/P(T-/A+) over
P(T+/A-)/P(T-/A-) is estimated. This OR is a good approximation of RR as long as the event in question is rare.
This chapter reviews the epidemiological studies which have attempted to answer these
questions, whether directly or indirectly. The retained publications concern, on the one hand,
research that provides significant results (Violenti and Marshall, 1996; Redelmeier and
Collective Expert Report
13/12/2011
Page 67
Tibshirani, 1997a and b; Violenti, 1998; Sagberg, 2001; Laberge-Nadeau et al., 2003; Wilson et
al., 2003; Sullman and Baas, 2004; McEvoy et al., 2005; Nabi et al., 2007; Young and Schreiner,
2009) and, on the other hand, research concerning methodological considerations allowing
for a critical look of some of them (Grender and Johnson, 1993; Marshall and Jackson, 1993;
Roberts et al., 1995; Redelmeier and Tibshirani, 1997b and 2001; Redelmeier et al., 2003;
Laberge-Nadeau et al., 2006; Braver et al., 2009; Gibson et al., 2009; Schouten and Kester,
2009). The other publications (Caird et al., 2004; McCartt et al., 2006; Brace et al., 2007;
INSPQ, 2007) are reviews of literature addressing epidemiological studies as well as many
experimental studies carried out in the laboratory. Finally, follow-up studies on vehicle fleets
in circulation, referred to as "naturalistic driving", will also be analyzed (Sayer et al., 2005;
Klauer et al., 2006; Olson et al., 2009). This entails research carried out using the observation
of vehicle fleets equipped with devices which allow the behavior of drivers in actual driving
situations to be monitored over long periods of time.
Finally, it is important to know the characteristics of the people who use cell phones while
driving, as the latter can be at the source of an increased risk of an accident which may not be
caused by mobile phone use itself. These characteristics must be taken into account as much
as possible during studies on the link between mobile telephony and road accidents.
Results of epidemiological studies on the association between telephoning
while driving and accidents
The ten selected studies summarized below are those on which the risk evaluations
presented afterwards will be based. These differ according to the populations studied, the
information available, protocols and the factors that they attempt to explain (table 5.II). These
differences are such that they do not allow a meta-analysis to be carried out. The first five
compare mobile phone owners, and therefore potential mobile phone users while driving, to
non owners. The next five compare accident victims who were telephoning (more or less
likely) at the time of the accident to accident victims who were not telephoning. Note that the
Laberge-Nadeau study (2003), which is one of the first five, is also mentioned in the second
group, as it is analyzed differently.
Violenti and Marshall (1996)
This study was carried out using follow-up data on driving licenses and mandatory
declaration data for personal injury and damage accidents (for damage exceeding $1,000)
that occurred in the state of New-York between 1992 and 1993. The authors formed two
groups of drivers: the group of cases that had at least one accident in the last two years
(N=60) and the randomly-selected group of controls (N=77) that had no recorded accident in
the last ten years. A questionnaire covering 18 behaviors associated with possible inattention
was sent by mail to each of the subjects.
Drivers who use their telephone at least 50 minutes per month have 5.6 times more risk of
being involved in an accident than the others. This odds-ratio (OR) is significantly different
from 1, and takes driving experience and indicators of motor and cognitive activities while
driving into account in the same logistic regression model.
However, these results were obtained for only 14 mobile phone users, and the authors
clearly specify that they do not know if the drivers were using their mobile phone at the time
of the accident.
Collective Expert Report
13/12/2011
Page 68
Wilson et al. (2003)
The study sample is comprised of two groups of drivers observed in 1999 in the district of
Vancouver that were seen telephoning while driving (about half of the sample) or not (the
other half of the sample). Data relating to insurance, violations and accidents was then linked
together for 3,869 of these drivers by the intermediary of the license plates of their vehicles,
in compliance with a strict protocol concerning anonymisation. The drivers retained are
those for which the age and the sex of the driver observed correspond to the characteristics
of the owner of the vehicle. A driver involved in a declared accident is considered to be "at
fault", using the claims declarations, if his responsibility is equal to or greater than 50% by
the insurance companies. This responsibility analysis approach entails comparing drivers
considered "at fault" to drivers who are not "at fault", i.e. involved in an accident "by chance",
and as such are considered as representing all of the drivers in circulation. If this principle is
admitted and if the determination of responsibility is considered to be sufficiently reliable,
this method makes it possible to benefit, for both groups to be compared, from information
of like quality, as it is coming from the same sources of information.
The main result of the study shows that drivers observed in the process of telephoning have
a higher risk of being "at fault" in an accident than drivers not observed in the process of
telephoning. The odds-ratio estimated at 1.16 (CI 95% [1.00-1.33]) is adjusted for age, sex,
measurement of an illegal blood alcohol level, the number of declarations of claims
considered without responsibility involved and the fact of having received fines for
violations considered by the authors as being associated with driving of the aggressive type.
Moreover, telephone users have more often committed violations linked to excessive speed,
not wearing seatbelts, an illegal blood alcohol level or aggressive driving.
The main weakness of the study comes from the lack of specificity as to the exposure to the
telephone, because it is not known if the drivers were telephoning at the moment the
accident occurred, and also because a portion (unknown) of drivers are incorrectly
considered as non telephone users simply because they were not telephoning when they
passed in front of the observers. A contrario, telephone users were seen telephoning while
driving and are not simple telephone owners as in other studies. The significant additional
risk is perhaps low due to the lack of specificity as to the exposure to the telephone. It may
also be only the reflection of risk behaviors of those who telephones while driving, even if
this estimate is adjusted for anumber of relevant behavioural factors.
Sullman and Baas (2004)
The main objective of this research was to establish a profile of drivers that use mobile
mobile phones in New Zealand, but an estimation of the risk of an accident was also
produced. This was a survey via a questionnaire distributed in urban petrol stations in 2003.
Among the drivers surveyed, 57% of the drivers stated that they use the mobile phone while
driving. These at least occasional users were most often men, heavy road users, having
recent cars, and young people. The risk of being involved in an accident over the last three
years is higher for a driver using the mobile phone while driving, but this result is no longer
statistically significant after adjustment for the various co-factors mentioned above (OR=
1.16; CI 95% [0.98-1.36]).
As in the previous article, the risk associated with telephoning while driving, without
knowing if its use was effective at the time of the accident, appears to be rather low, and this
all the more so in that the users are also drivers that seem to have more risk behaviors than
non-users.
Collective Expert Report
13/12/2011
Page 69
Laberge-Nadeau et al. (2003)
More than 175,000 driving license holders were contacted via a postal questionnaire in
Quebec in the years 1996 to 2000. Of these holders, 36,078 signed a consent letter and fully
completed the questions covering their exposure to driving, their driving habits, their
opinion concerning certain factors estimated to be at risk for the driving activity and the
possible occurrence of accidents in the last 24 months. This data was then linked to the data
of the four mobile phone operators in Quebec, in order to have information on cell mobile
phone use "continuously" over the two years, to the information in the insurance files of the
SAAQ (which collects all of the accident declarations in Quebec, including damage
accidents), and to the police accident reports. The risk of having a damage or personal injury
accident is significantly higher for cell phone owners than for non-owners (RR=1.38; CI 95%
[1.28-1.50]). This relative risk is equal to 1.11 for men and 1.21 for women once adjusted for
the distances traveled and for factors associated with driving habits. According to the
authors, the most remarkable result of this study is the identification of a dose-effect ratio
between the frequency of mobile phone use and the risk of an accident.
In light of its extent, the quality of the data available and the care taken in analyzing it, this
study is unquestionably one of the most important concerning the question of telephoning
while driving. However, as in the previous studies, it is based on the difference between
mobile phone owners and non-owners, without knowing if the mobile phone owners were
using it at the time of the accident. An additional analysis of this data was then carried out,
and is detailed further on, as it uses case crossover analysis of which the principle is explained
for the Redelmeier and McEvoy studies.
Nabi et al. (2007)
The Gazel cohort is comprised of employees and new retirees of the EDF and GDF
companies. In this cohort, 13,447 (68%) of the participants answered a questionnaire in 2001
covering their behavior on the road in terms of speeds habitually driven according to road
type, on driving after drinking or in a state of drowsiness, on the frequency of violating
traffic rules or on the use of their mobile phone while driving. Three responses were possible
for the latter question: never, yes but in "suitable" circumstance or stopping in order to make
a call, yes regardless of the circumstances. A new questionnaire was sent in 2004 comprising
in particular information on any possible road accidents that occurred in the interval. The
responses indicate that 337 participants had an accident involving bodily injury within the
three years. The risk of having an accident is estimated to be multiplied by 1.73 (CI 95%
[1.09-2.74]) for drivers declaring using their mobile phone while driving regardless of the
driving circumstances in comparison with non-users, although this risk is not significantly
different from 1 for those declaring that they stop or that they answer only in the case of
circumstances that they feel are suitable. These relative risks are adjusted for co-factors
deemed significant such as the speeds practiced in urban or rural areas or on the highway,
the tendency towards behavior to commit violations and driving sometimes in a somnolent
state.
As the drivers surveyed in this study were relatively old, they are not part of the population
most at risk of having a road accident, and those who use cell phones the most. However, the
additional risk of an accident, determined over a rather large sample, has the interest of
distinguishing two types of behaviors with regards to mobile phone use, being evaluated
prospectively (the questions on the behavior preceded the occurrence of accidents), being
adjusted for many pertinent factors, and being evaluated over a French population.
Collective Expert Report
13/12/2011
Page 70
Violenti (1998)
This study was carried out in the state of Oklahoma for the years 1992-1995, using police
accident records wherein are noted the presence of a cell phone on board the damaged
vehicle, and its possible use at the time of the accident evaluated by the police. The study
compares drivers killed (65 cases) and drivers that were not killed (1,483 controls) involved
in fatal accidents. Among all of the drivers, 65 had a mobile phone on board and 5 were
using it when the accident occurred. Once adjusted via logistic regression over the sex, age,
blood alcohol content, speed violations, an inattention indicator and the fact of not keeping
to the right, the risk of being killed in a fatal accident is higher for a driver with a mobile
phone on board (OR=2.11; CI 95% [1.64-2.71]), and much higher for a driver who was
supposedly having a mobile phone conversation at the time of the accident (OR=9.0; CI 95%
[3.7-23]).
The author states that the hypothesis at the origin of the study is not that the mobile phone
directly affects the risk of being killed, but that the mobile phone increases the probability of
the presence of certain characteristics of the accident in association with its seriousness.
The strength in this study is the knowledge of the mobile phone use at the time of the
accident. However, this information, obtained by the police, is without a doubt an underevaluation of reality. Moreover, mobile phone users were, at that period in time, only a small
number. The fact of working using fatal accidents is a guarantee of better quality for the
information collected, but the relative risk of being killed rather than injured for a driver
involved in a fatal accident is not the one that is of most interest. It makes it possible,
nevertheless, to raise the question of knowing whether or not, in addition to affecting the
occurrence of an accident, the fact of telephoning while driving modifies the consequences of
the accident in terms of gravity.
Sagberg (2001)
Using files from the two largest Norwegian insurance companies, a questionnaire was sent to
owners of vehicles involved in accidents in 2001. The questions addressed the characteristics
of their latest accident and on the possible use of a cell phone during this accident. The
anonymous questionnaires were sent to TOI (Transport economics institute). As for the
Wilson et al. study (2003), responsibility in the accident was determined by the insurers.
According to the approach referred to as "quasi-induced exposure" (Stamatiadis and Deacon,
1997; Lenguerrand et al., 2008), the analysis compares the 3,340 drivers considered
responsible with the 2,966 non-responsible drivers, by testing if the proportion of those who
were telephoning when the accident occurred is different in these two groups. Adjusted for
many factors such as the annual distance, sex, age or whether there was a passenger in the
vehicle, the risk for a driver of being responsible for an accident was multiplied by 2.37
(CI 95% [1.02-5.48]) when he was telephoning at the time of the accident. The risk associated
solely with a hand-held mobile phone is higher, but the statistical power of the study
prevents making a clear conclusion as to a possible difference according to the type of mobile
phone used.
The author recognizes that it is possible that the proportion of drivers who declared that they
were telephoning during the accident is under evaluated, but that this under-declaration has
no consequence on the conclusions of the study since it is independent of the responsibility
attributed elsewhere. It is also possible that the drivers considered as non-responsible and
who were telephoning had a share in the responsibility, with the mobile phone use having
reduced their ability to avoid an accident wherein another driver was held responsible, or
the mobile phone use having caused a dangerous behavior that was difficult for the other
Collective Expert Report
13/12/2011
Page 71
users to take into account (suddenly slowing down without any apparent reason). This tends
towards an under-estimation of the risk attached with mobile phone use.
This study has the advantage of being based on the knowledge, which can be considered as
reliable, of the mobile phone use at the time of the accident, but is based on only a small
number of drivers telephoning. Note that a similar study carried out by the same research
team has just been published (Backer-Grondahl and Sagberg, 2011), and yields results that
are close, but only address accidents involving several vehicles.
Young and Schreiner (2009)
A cohort of vehicles equipped with an "On-Star system" wireless mobile phone system built
into the vehicle was followed from June 2001 to November 2003. The database compiled
included the counts, instants and durations of all incoming and outgoing communications as
well as the calls placed in the event of a triggering of the front airbag equipping each car.
During the 30 months of monitoring about 200,000 vehicles, 14 airbag deployments for 276
million minutes of driving were recorded while the drivers were in the process of
telephoning, to be compared with 2,023 for 24.7 billions of minutes of driving corresponding
to drivers that were not telephoning at the time of the accident. The ratio of these two
incidence rates, the IRR, is as such estimated to be 0.62 (CI 95% [0.37-1.05]), i.e. not
significantly different from 1.
The major strength in this study is simultaneously knowing the mobile phone activity with
very good precision with the on-board system and the instant the accident occurred with the
triggering the front airbag. The time spent on the mobile phone aboard the vehicle is also
known, and the time spent without telephoning is estimated using the distance and the
average speed of the fleet of vehicles equipped with the On-Star system.
However, no data is available on the possible use of a personal cell mobile phone.
The authors indicate that the study of this cohort of three million drivers over 30 months
does not show any additional risk of an accident triggering a front airbag. Observing that
their study produces results that differ from all of the others, they do no claim that their
conclusions can be applied without precaution to the effect of cell mobile phones, and
suggest that it is possible that this absence of additional risk comes from a particularly
cautious behavior on the road of the drivers when they are using their on-board mobile
phone system.
Also note that one of the authors of this article with highly rigorous methodology was part of
the General Motors company and the other for the On-Star company when the study was
carried out.
Redelmeier and Tibshirani (1997a and b)
People in the region of Toronto coming to a declaration center for road accidents with
damage between July 1994 and August 1995 were solicited to be included in the study.
Consenting subjects filled out a questionnaire on their characteristics and the circumstances
of their accident. The detail of the communications by cell phone of each driver was
provided by the operators for the day of the accident and the seven days before (times,
durations, incoming or outgoing calls, calls to the police or emergency services). The instant
of the accident was estimated using the declaration of the drivers, the police report and
emergency call statements. In the event of an incoherency with these estimations, the most
precocious instant was retained, in order to avoid as much as possible attributing to the
period before the accident a call that took place afterwards, as such confusing the potential
Collective Expert Report
13/12/2011
Page 72
cause and the consequence. A variation in case-control studies, referred to as case crossover,
was used to analyze this data. The principle is to compare the exposure to the mobile phone
of each driver during the period just before the accident to an equivalent period of time at a
distance from the accident. Each subject is as such considered as his own control, which
allows for an adjustment for the age, sex, visual acuity, experience, personality and all of the
characteristics of the drivers that are invariable in the short term. By using data matching
analysis techniques such as conditional logistic regression, the analysis as a case crossover
thus makes it possible to test a possible increase in the risk of an accident if the number of
mobile phone calls immediately before the accident is higher than it is in other comparable
periods. The period preceding the accident by 10 minutes is as such compared to the same
period the day before (same hour, same minutes). Four other control periods are also used:
the last day of the week preceding the accident (excluding the weekend), the same day of the
previous week, the most recent day of the previous week if there was mobile phone activity,
the day among the three previous days during which there was the most mobile phone
activity.
One of the difficulties with the method is that, although the driving activity is certain during
the period preceding the accident (even if it cannot cover this entire period), this is not true
for the control periods. In order to take this into account, the authors took an additional
survey of 100 subjects, with which they deduced that on the average the control periods are
periods of driving in 65% of the cases. The relative risk estimates are therefore divided by 1.5
(1/0.65) in order to take the intermittence of driving into account. Note that this correction
leads the authors to provide confidence intervals for the relative risks using the bootstrap
method.
The study as such involves 699 drivers for whom all of the pertinent information is available.
By using the "main" control period, the odds ratio is estimated to be 4.3 (CI 95% [3.0-6.5]) by
applying the correction for the intermittence of the driving, and 7.0 (CI 95% [3.7-15.5]) for a
sub-sample of drivers declaring that they are certain they had driven during the control
period. The estimations are not very different by 4 by using the four other control periods.
The OR is significantly higher (5.4) for accidents on highways than for accidents on parking
lots (1.6). The OR associated with hands-free telephoning (5.9; CI 95% [2.9-24]) is not
significantly different from that for hand-held telephoning (3.9; CI 95% [2.7-6.1]). Finally, the
OR is equal to 3.0 using only incoming calls, and to 3.8 using only outgoing calls.
The protocol for this study is particularly suited to the type of event of interest, characterized
by an intermittent exposure to the presumed factor at risk, cell mobile phone use, and an
immediate effect on the occurrence of the event, the accident, without latency or remnant
effect. Data matching makes it possible to take into account a large portion of the
characteristics of the drivers without explicitly measuring them. The estimated risks are as
such more specific for the possible "telephoning while driving" effect by eliminating a
considerable portion of the variability due to the driver. The weak point in the study is the
taking into account of the intermittence of driving which appears to be very roughly done.
Much effort was made by the authors to know the exact moment of the accident, without
however being certain to avoid the major pitfall which consists in classing prior to the
accident calls that were made afterwards, especially since the number of calls after the
accident is shown to be very high (which can clearly be classified as a benefit of the mobile
phone). With this, the result using only incoming calls avoids a large part of this possible
confusion.
Finally, a last point raises an issue: the mobile phone conversation for the participants in the
study was 2.3 minutes on the average, and 75% of these communications did not exceed
2 minutes (which corresponds to the average of the durations of mobile phone conversations
Collective Expert Report
13/12/2011
Page 73
at the time outside the driving context). Figure 5.1 shows the OR according to the time
elapsed between the call and the collision.
Figure 5.1: Relative risk of an accident according to the time elapsed between the mobile phone call
and the collision
This figure shows that the risk of an accident associated with the mobile phone increases
with the probability that the driver was actually telephoning at the instant of the accident.
The proposed analysis thus makes a compromise between two possible biases:
• incorrectly attributing to the mobile phone the occurrence of the accident when the
driver had already hung up;
• incorrectly attributing a mobile phone call after the accident, a fact which is especially
more likely as the period taken into account before the accident is of short duration.
Although it can be considered that the authors have almost entirely avoided the second bias
through the special care that they have taken, they were certainly not able to avoid the first
one which is intrinsic to the method. This bias classification results in an under-estimation of
the risk (Redelmeier and Tibshirami, 1997), an under-estimation that is even higher as the
number of drivers incorrectly considered as telephoning is high (Greenland, 1982; Greenland
and Kleinbaum, 1983). Note that the strengths and weaknesses of case crossover studies have
been widely discussed by the authors in other more methodological articles (Redelmeier and
Tibshirani, 1997 and 2001; Tibshirani and Redelmeier, 1997).
McEvoy et al. (2005)
In the region of Perth in Australia, between April 2002 and July 2004, drivers involved in
accidents of moderate seriousness were recruited when they came to an emergency service.
Among those involved in an accident, 744 drivers agreed to answer a questionnaire and
provide access to their data concerning the accident and their mobile phone usage
information. Only the 456 drivers who declared that they had driven during the control
periods were finally included in the case crossover study. The instant of the accident is
determined using the driver's declaration, data from the emergency services and medical
data. In the event of an incoherency, the most precocious instant is retained. The "case"
period contains the 10 minutes prior to the accident, the control periods are comprised of the
"same" 10 minutes the day before, 72 hours before and one week before.
Collective Expert Report
13/12/2011
Page 74
The risk of being involved in a personal injury accident for a driver who had a high
probability of being in the process of telephoning, compared to a driver who was not
telephoning, is estimated to be multiplied by 3.7 (CI 95% [1.5-9.0]) by taking the day before
(D-1) as a control period, 4.7 (CI 95% [1.3-16]) with D-3 and 4.5 (CI 95% [1.9-11]) with D-7. As
these estimates are very close, the OR retained is 4.1 (CI 95% [2.2-7.7]) by using all of the
control periods during which each subject declared having driven. The risk associated with
the use of a hands-free mobile phone is 3.8 (CI 95% [1.8-8.0]), which is not significantly
different from that associated with a hand-held mobile phone, 4.9 (CI 95% [1.6-15]).
This study has the same strengths and weaknesses as the Redelmeier case crossover study.
Data matching makes it possible to obtain an estimation of the relative risk that is more
specific to mobile phone use, since it is adjusted for a large part of the individual factors for
drivers. The authors, in addition, have taken into account the possibly delay shorter than
10 minutes before the accident (and consequently adjusted the control periods). However, as
in the Redelmeier study, since only volunteers were included in the study, it is possible that
those who refused have different behaviors with regards to driving and mobile phone use
while driving than those who agreed to participate. It is also possible that certain drivers are
in error when they affirm having driven in the control periods. Here again, the authors were
very careful to avoid classifying calls after the accident as occurring before the accident,
without however fully throwing this risk aside. Finally, mobile phone use such as defined in
these two studies includes dialing, conversation and the use of SMS. As the latter practice
was not very common when these two surveys were taken, the practice of SMS probably has
little weight in estimating risks.
Although during the 8 years that separate these two studies, mobile mobile phone use while
driving increased substantially in Australia as in the United States, the estimated odds ratios
are of the same order of magnitude, whether concerning the additional risk for a driver
telephoning while driving of being involved in a damage accident, or of being involved in a
"light" personal injury accident.
It can also be noted that many more calls were recorded in the period before the accident in
the Redelmeier study than in the McEvoy study. It is possible that this is due to the fact that
in Australia in 2002, a law banned the use of hand-held mobile phones, which was not the
case in Canada in 1995.
Laberge-Nadeau et al. (2006)
A re-analysis of the data for the mobile phone users mentioned above (Laberge-Nadeau et al.
(2003) was proposed using the case crossover methodology. The "case" period ranges from
ten minutes to one minute before the accident, the control period corresponds to the same
period of time the day before. Emergency calls are not taken into account as they could be
consecutive to the accident. A total of 407 accidents (of which one-fourth were with bodily
injury) were reported by the police during the two years for which mobile phone statements
were available. The relative risk is 5.13 (CI 95% [3.13-8.43]), without correction for the
intermittence of driving in the control periods.
The authors draw attention particularly to the issue raised by the lack of precision
concerning the instant of the accident, for which the time indicated often seems rounded to
the nearest five minutes, which could lead to a substantial overestimation of the risk due to
taking possible calls after the accident into account.
Collective Expert Report
13/12/2011
Page 75
Table 5.II: Main studies estimating the risks associated with mobile phone use while driving
References
Type of study
Years of
Location
collection
Populations
compared
Size
Source
Associated relative
risk estimates
[Confidence
intervals at 95%]
Knowledge of
mobile phone
use at the time
of the accident
Weaknesses
Strengths
Violanti and
Marshall, 1996
Case-control
19921993
State of
New-York
Involved in an
accident versus
not involved in
an accident
60/77
Police accident
record +assurance +
survey by mobile
phone for risk
factors
OR=5.59 [1.19-37.3]
No
Only 14 users of the
mobile phone, additional
risk with years of
experience
Analysis matched on the place of
residence, adjusted for other
activities while driving
Wilson et al.,
2003
Exposed/nonexposed cohort
1999
Canada,
Vancouver
Drivers deemed
1,876/
responsible versus 1,993
not responsible
Insurance
companies for
accidents and
observation at the
edge of the road for
the mobile phone
OR=1.16 [1.00-1.33]
No
Lacks specificity as to the
exposure to the mobile
phone, Depends on the
quality of determining
responsibility
Groups passing at the same
locations and times, drivers "at
fault", adjustment for many cofactors, including "aggressive
driving"
Sullmann and
Baas, 2004
Transversal
2003
New
Zealand
Involved in an
accident in the
last five years
versus others
344/517
Survey via
distributed
questionnaires
OR= 1.16 [0.98-1.36]
No
Lacks specificity as to the
exposure to the mobile
phone
Especially the description of users
or non-users of the mobile phone,
including the use of a "hands-free"
system
LabergeNadeau et al.,
2003
Exposed/nonexposed cohort
19962000
Quebec
Mobile phone
users versus nonusers
12,681
/23,387
for
141,350
personsyears)
Telephony operator
records + Insurance
companies (damage
and personal injury
accidents)
RR men =1.11 [1.021.22]
RR women= 1.21
[1.03-1.40]
For hand-held
mobile phone versus
hands-free mobile
phone:
RR men =1.23 [0.861.78]
RR women= 1.24
[0.37-4.15]
No
Lacks specificity as to the
exposure to the mobile
phone, Participant
consent, leading to
possible bias
Objective measurement of the
mobile phone, direct access to the
RR, adjustment for many co-factors,
including distance travelled, higher
risk for power users in relation to
low-use users (dose-effect ratio)
Collective Expert Report
Page 76
13/12/2011
Nabi et al., 2007 2001
Prospective
cohort
France
Drivers involved
in an accident
with bodily
injury between
2001 and 2003
versus those not
involved in an
accident
328/
13,447
Cohort of 19,894
EDF-GDF
employees recruited
starting in 1989
RR call or response
regardless of the
driving
circumstances=1.73
[1.09-2.74]
No
Attitude faced with the
risk, not the risk of
telephoning
Participants over the age
of 50, which reduces
prevalence
Adjustment for behaviors at risk
Follow-up of the occurrence of
accidents within three years
according to the declarations on
behaviors
Violanti, 1998
Case-control
State of
Oklahoma
Drivers killed in
an accident versus
not killed
65/1,483
Police accident
record
OR presence mobile
phone=2.1 [1.6-2.7]
Yes (according
to police)
Risk of being killed
among those involved in
an accident, not to be
involved in an accident
(interesting, but
different), very few
mobile phone users
Many adjustments
19921995
OR mobile phone
during accident=9.3
[3.7-23]
Sagberg, 2001
Case-control
(quasi-induced
exposure)
2001
Norway
Drivers deemed
3,340/
responsible versus 2,966
not responsible
Questionnaire
OR=2.37 [1.02-5.48]
Yes (driver
declarations)
Low number of drivers
telephoning (31)
Depends on the quality
of determining
responsibility
Anonymous response to the
questionnaire, supposedly allowing
for good quality answers on mobile
phone use
Pertinent adjustments
Determination of responsibility by
the insurance companies
Young and
Schreiner, 2009
Cohort
20012003
United
States
Mobile phone
during the
accident versus
non-mobile
phone during the
accident, among
users of handsfree mobile
phone service
14 /2,023
(for 250 M
minutes
driven)
Vehicles equipped
with "On-Star"
hands-free mobile
phone system,
continuous
collection, accidents
if triggering of front
airbag
IRR=0.62 [0.27-1.05]
Yes (objective
measurement)
Low number of events,
population very
particular, author
independence is
questionable, particular
type of accident, no cofactor adjustments
Perfect measurement of the
moment of the accident and of the
"On-star" mobile phone use, direct
access to the ratio of the incidence
rates
Region of
Toronto,
Canada
Mobile phone
within 10 min
preceding the
accident versus
same drivers,
another 10 min
period
699 (170
callers
before the
accident)
Telephony operator
records + Assurance
(damage and
personal injury
accidents)
OR=4.3 (3.0-6.5)
Hand-held=3.9 (2.76.1); hands-free=5.9
(2.9-24.0)
Incoming calls=3.0
Outgoing calls=3.8
Yes, with the
problem
concerning the
precision of the
moment of the
accident
Rather rough taking into
account of intermittence,
no certainty as to the
action of telephoning at
the time of the accident,
inclusion of volunteers
only
Distinction between incoming and
outgoing calls, major effort to know
the instant of the accident and
avoid classification error, stability
of the results by varying the period
of comparison, coherency of the
sub-analyses, taking into account of
other possible factors (not
measured) concerning distraction
Redelmeier and 1994Tibshirani,
1995
1997a and b
Case-crossover
Collective Expert Report
Page 77
13/12/2011
McEvoy et al.,
2005
Case-crossover
20022004
Perth,
Australia
Mobile phone
within 10 min
preceding the
accident versus
same drivers,
another 10 min
period
456 (32
callers
before the
accident)
LabergeNadeau et al.,
2006
Case-crossover
Reanalysis
Same data
Mobile phone
within 10 min
preceding the
accident versus
same drivers,
another 10 min
period
407
involved
in an
accident
Collective Expert Report
Telephony operator
records + care
services (personal
injury accidents)
Page 78
OR=4.1 [2.2-7.7]
OR hand-held=4.9
[1.6-15.5]
OR hands-free=3.8
[1.8-8.0]
Yes, with
comparison of
different
sources and
taken into
account if
coherent
Recall bias possible on
effective driving during
the control periods. No
certainty as to the action
of telephoning at the time
of the accident, inclusion
of volunteers only
OR=5.1 [3.1-8.4]
Yes, with the
problem
concerning the
precision of the
moment of the
accident
No correction for driving
intermittence. Major
doubt expressed by the
authors as to the
precision of the instant of
the accident, leading to a
likely overestimation.
13/12/2011
Stability of the results by varying
the comparison period, coherency
of the sub-analyses, taking into
account of other possible factors
(not measured) concerning
distraction. Taking into account a
delay that is possibly shorter than
10 min before the accident (63% of
drivers were driving for 10 min or
less at the time of the accident)
Follow-up studies of vehicle fleets in circulation
Between experimental studies and epidemiological studies, fleet follow-up studies of drivers
in a "natural" driving situation can provide elements for interpreting risks associated with
telephoning while driving. Four American studies have retained our attention.
The Klauer et al. study (2006) is that for which the results are the most often included in
literature reviews mentioned elsewhere. This is a follow-up study for 12 months of 109 cars
equipped in such a way as to be able to observe the behavior of drivers and the occurrence of
accidents, "near accidents" and incidents. The interest with this type of study is that it makes
it possible to observe the many secondary tasks (with the first being the task of driving) that
are performed by drivers, in actual driving situations. As such, the risks are produced of
being involved in an accident or a "near accident" associated with the various secondary
tasks. A hierarchy of the various tasks is proposed, with the most risky being for example
those for reaching an object that is far away, handling the presence of an insect, looking at an
outside object, reading or dialing a mobile phone number on the device held in the hand. The
odds ratio associated with mobile phone conversation is greater than 1, but is not significant.
The Olson et al. study (2009) uses the same methodology for 203 drivers of heavy trucks en
by gathering the data from two follow-up studies. Here too, a classification of the tasks
according to their dangerousness is offered, with the most risky task being that of writing a
message on a cell phone, with mobile phone conversation not being significantly deemed at
risk.
There are two main difficulties however as to interpreting these results. The first is that the
event in question is not the occurrence of an accident, as the phenomenon is too rare in the
two studies to be able to obtain reliable risk estimates, but the accident or "near accident" in
the first study, and the accident, "near accident", or a major unintentional deviation of the
trajectory in the second. Although the authors' intention of increasing the statistical power
appears to be legitimate, considering the near accident, and even the unintentional trajectory
modification as events foreshadowing an accident is not direct, and especially has to depend
on many factors, including the secondary activity type. Note that a study describing the
effect of the use of near accidents instead of accidents has just been published by the same
research team (Guo et al., 2010). The other defect is of a calculative nature: the authors do not
take into account in calculating their confidence intervals the correlation that exists between
the measurements taken on the same individual, which produces an under-estimation of the
variances and can lead to incorrectly concluding that certain effects are significant.
The Sayer et al. study (2005) avoids the latter pitfall, but is also lacking in statistical power as
it only relates to 36 vehicles. It is however interesting to note that the action of telephoning
does not seem to substantially modify the holding of the trajectory, but it seems to increase
braking reaction time, which conforms to experimental results.
The very recently published Hickman et al. study (2010) includes a much higher number of
vehicles. Indeed, the analysis covers 13,306 vehicles followed for 3 months. In this study,
1,085 vehicles involved in damage and bodily injury accidents are observed, but the main
estimations produced relate to the risks associated with events defined as critical, not to the
occurrence of accidents. The results obtained are coherent with the Olson study, the dialing
of a number or taking a mobile phone in the hand or earpieces being associated with an
additional risk of a "critical safety event" occurring (significant odds ratios estimated to be
3.5), while hands-free mobile phone conversation is associated with a risk of a significant
critical event for drivers of buses (OR=1.3) and with a protective effect for drivers of semitrailers (OR=0.6).
Collective Expert Report
- 79 -
13/12/2011
The two difficulties in interpreting statements for the other studies hereinabove exist here
too. It can in particular be observed that among the 37,708 events identified as able to
provoke an accident, only 1,064 (2.8%) are really associated with the occurrence of an
accident. In other words, the vast majority of events considered in calculating odds ratios do
not result in the occurrence of an accident. In addition, as the authors themselves indicate,
the definition of the relative risk reference levels is not very satisfactory and can result in
underestimating them. Finally, this study covers a very particular population, of professional
bus and heavy trucks drivers, who accepted to be under video surveillance during all of their
travel. The generalization of the results obtained on American professional drivers of heavyduty vehicles cannot be direct.
In the current state of the publications, it seems that these "naturalistic driving" studies have
the major advantage over the aforementioned epidemiological studies in allowing for a
distinction of the various tasks that can distract the driver from his task of driving, especially
during mobile phone use (dialing a number, conversing, reaching for the mobile phone, etc.),
proposing estimates of the risk of a critical event occurring (of which some can be considered
as being associated with the occurrence of an accident) and above all in prioritizing them,
with composing an SMS seeming, for example, to be associated with a very high risk. It is on
the other hand difficult to deduce reliable estimations from this of the risks of accidents
associated with mobile phone use while driving in actual driving situations for all users as a
whole.
Methodological approach of the studies and proposal of an estimated risk
The four recent literature reviews (Caird et al., 2004; McCartt et al., 2006; Brace et al., 2007;
INSPQ, 2007) which address the effect of telephoning while driving, or more generally the
"distraction" factors of driving, are primarily based on the same studies as those analyzed in
this research, except for the Sagberg article that was published in a rather marginal journal in
the field and that of Young and Schreiner which was not published until 2009. Also note that
all of the research included covers mobile phone use while driving primarily by drivers of
private vehicles, and more rarely drivers of heavy trucks or utility vehicles. None of them
addresses the effect of the mobile phone on driving for drivers of other types of vehicles or
on the behavior of pedestrians crossing the road. Most of these studies were carried out
before the effective date of certain laws reprimanding the use of the hand-held mobile
phone.
The Wilson et al. (2003), Sullmann and Baas (2004) and Laberge-Nadeau et al. (2003) studies
address the question "do mobile phone owners have a greater tendency to have accidents
than others?". These studies were carried out at a period in time of a low equipment rate, and
the people who then owned a cell phone most certainly had socioeconomic characters that
are different from others, and therefore different ways of using their vehicles. The authors of
this research produced relative risk estimates adjusted for a portion of these characteristics.
As such, in order to try and isolate the effect itself of the mobile phone, estimations of oddsratios are adjusted, among other things, for the sex, age and distance traveled in the LabergeNadeau and Sullmann studies. As expected, this adjustment lowers the starting raw
estimates, and any additional risks are low, between 1.10 and 1.20, but significant. The
Laberge-Nadeau study shows in addition that drivers frequently using the mobile phone
had a risk of an accident higher than those who used it little, which constitutes an element in
favor of a possible causal interpretation. In the Wilson study, the estimated OR is of the same
order of magnitude although it is not adjusted for the distance but for an indicator of driving
referred to as aggressive, defined using the violations listed. Another difference is that it
Collective Expert Report
- 80 -
13/12/2011
compares drivers considered "at fault" with drivers which are considered as involved by
"bad luck", and in itself constitutes controls for drivers in circulation. Although the
disadvantage on the approach is to have to use the definition of responsibility which is often
difficult to establish, it does have the advantage of comparing "at fault" drivers to driver
controls subjected to the same traffic conditions when they are involved in the same accident.
Of these various studies, it can be retained that the risk of an accident associated with the
possibility of telephoning while driving is estimated to be between 1.10 and 1.20, keeping in
mind that this is an average value for all drivers as a whole who use their mobile phone
while driving, some using it only very rarely, and others for a major portion of their travel.
The Nabi et al. (2007) study provides additional precision by distinguishing, on the one
hand, drivers who declare using the mobile phone while driving only when the driving
conditions so allow and, on the other hand, drivers declaring the use regardless of the
circumstances. The risk of 1.7 associated with the second compared to non-users, concerns
less than 10% of mobile phone users. If we consider that the first do not have a significant
increase in the risk of an accident in relation to non-users, the value of the risk associated
with all mobile phone users, i.e. 1.7x10%+1x90%, which is 1.07, is of the same order of
magnitude as in the previous studies.
Contrary to the previous research, the Redelmeier and Tibshirani (1997a and b) and McEvoy
et al. (2005) case crossover studies strive to estimate the risk of an accident for a driver in the
process of telephoning in relation to a driver who is not telephoning. It is therefore natural
that risks found are higher than the previous ones, between 3 and 5 according to the studies
and the sub-groups studied. Note that these studies do not distinguish between mobile
phone conversations and sending SMSs. This latter practice was almost non-existent at the
time of data collection in the Canadian study, and still uncommon for the Australian study,
and this amalgam without a doubt has little effect on the results.
The main problem linked to this type of study is the risk of attributing mobile phone calls
that occurred after the accident to the period preceding the accident, due to the imprecise
knowledge of the instant of the accident. This confusion between cause and effect would
indeed have many consequences, as all of the studies show that the number of calls after the
accident is very high. In the McEvoy study, for example, half of the accident victims use their
mobile phone after the accident. In addition, and although this entails personal injury
accidents, the calls are primarily made to members of the family (65%), friends, the
workplace, with calls to emergency services (31%) then being made. This means that the
precaution of excluding emergency calls is necessary but is not enough to fully avoid taking
calls due to the accident into account. However, the Redelmeier and McEvoy studies have
done everything possible to avoid this classification bias: both studies exclude emergency
calls and retain the drivers only in the case of coherency between the sources of information
concerning the instant of the accident. Especially, the OR attached to incoming calls is the
same as that attached to outgoing calls for Redelmeier, which is a very strong argument in
thinking that this classification bias was avoided for the most part.
Another point to take into consideration is that the statistical association identified may not
be causal: the driving conditions (inclement weather, driving in a major hurry or with
emotional stress, etc.) can contribute to the occurrence of an accident as well as mobile phone
use. Comparing a driver to himself makes it possible to adjust the risk estimations on the
"stable" characteristics of an individual, but does not make it possible to adjust for driving
conditions which can be different between the periods that are compared, concerning the
environment of the driver as well as his faculties at the time. It is for example impossible to
adjust for blood alcohol content, which can be estimated only at the time of the accident,
while driving under the influence of alcohol can influence the risk of an accident as well as
Collective Expert Report
- 81 -
13/12/2011
mobile phone use. Here again, Redelmeier's taking only incoming calls into account is of
great importance. And of course the appearance of a causal relation comes from the results of
experimental studies which provide an explanation for the mechanism creating a disorder in
attention that is unfavorable to the task of driving.
Finally, the applied method consists in comparing periods during which the driver made or
received a call, without knowing whether he was still telephoning at the time of the accident.
The possibility of an incorrect classification introduces a non-differential bias if it is admitted
that the classification error is the same for the periods immediately before the accident and
the control periods. This bias seems to result in an over-estimation of the risks which is not
discussed by the authors.
With a very different methodology based on comparing drivers deemed "at fault" and those
that are not, Sagberg arrives at an estimation of the relative risk of 2.4, which is without a
doubt an under-estimation given the method used. As such, if we take it that case crossover
studies tend to overestimate the risk, the choice of a value around 3 seems reasonable for the
rest of the calculations.
Moreover, in most of the research that has studied the characteristics of accidents associated
with mobile phone use, a slight over-representation has been shown for accidents with rear
impact, with the telephoning driver hitting the rear of another vehicle by "distraction". This
type of accident can have certain specifics in terms of seriousness, as the associated risks can
then be different according to the criterion of seriousness which of interest (damage, bodily
injury, fatality). In favor of this hypothesis, the only study available is that if Violenti from
1998, but it has many weaknesses. The Redelmeier and McEvoy studies, one explaining the
occurrence of damage accidents, and the other personal injury accidents, yield results that
are close, the risks of being involved in an bodily injury or damage accident according to
whether or not one is telephoning while driving will not be distinguished.
Finally, and before proposing risk estimations to be retained, note that we have not taken the
results of two studies into account: that of Violenti carried out in 1996 which, despite a
pertinent protocol, has a statistical power that is too low, and the Young and Schreiner study
(2009), which benefits from exposure data of high precision, but which relates to a hands-free
system produced by a single manufacturer, which is not aware of the possible use of a
personal cell mobile phone and which has risk estimations that are not adjusted for
important factors.
Moreover, although this latter study could be put forth as an argument in favor of hands-free
systems, none of the epidemiological studies that compare the two modes of use show a
significant difference between the risk associated with the hand-held mobile phone and that
associated with the different existing hands-free devices. The hand-held mobile phone
always represents a higher risk, but not enough to have a difference that is statistically
significant in the various studies. The so-called "naturalistic driving" studies seem to indicate a
higher risk associated with dialing a number on a hand-held mobile phone, which is highly
coherent with experimental studies. Epidemiological studies do not allow for a distinction
between discussion phases and dialing phases, with the estimated relative risks therefore
concerning all of the phases of mobile phone use.
Estimation of the relative risk and of the attributable risk to mobile phone
use while driving
Finally, two estimations of relative risks can be retained:
Collective Expert Report
- 82 -
13/12/2011
• the first, between 1.1 and 1.2, represents the average risk of an accident for a driver
likely to mobile phone while driving, in other words telephoning during a portion of his
driving time;
• the second estimation, around 3, represents the risk of being involved in a damage or
bodily injury accident for a driver telephoning in relation to a driver who is not
telephoning, and this regardless of the system used (hands-free or otherwise). This is the
additional risk taken by the driver at the time when he is telephoning in his vehicle. So, it
is important to know what proportion of his travels is concerned by this increase in risk.
Two ways of approaching this value are used. According to a certain number of surveys
(details are provided in other chapters), between 2 and 6% of drivers have been seen
telephoning while driving. This figure obviously depends on several factors, such as the
equipment rate in mobile phones which has developed substantially, whether the current
law is more or less complied with or the equipment rate for hands-free systems which escape
observation. According to the survey carried out in France in 2007 (Onisr, 2008), 2.4% of
drivers were seen with a mobile phone in their hand while driving. According to other
elements in this survey, 41% of drivers who sometimes mobile phone while driving hold it in
their hand, with the other 59% using a hands-free system, including earpieces. If a
hypothesis is made that communication times are similar regardless of the system used, the
2.4% of drivers seen with the mobile phone in hand would correspond to 3.5% of the drivers
telephoning with a hands-free system. The overall prevalence for mobile phone use while
driving would therefore be of a magnitude of 6%.
In light of these estimations, on the average for a given journey, a driver mobile phones for
about 6% of the travel time, time during which he multiplies his risk by 3, and during the
remaining 94% of the time, he is at the basic risk (equal to 1 by definition). In other words,
his average relative risk is 6%x3+94%x1, which is 1.1, the value found for the relative risk
associated with mobile phone owners. If we take in general the high values, with a driver
who mobile phones 10% of the journey and a relative risk of 4, we obtain 1.3 for the Average
RR. These estimations show that there is a coherency between the estimated relative risks in
the two major types of studies that have been reviewed.
Using these values, an attributable risk (AR) can also be estimated, in other words the
proportion of accidents due to the exposure, with PE being the prevalence of mobile phone
use:
AR =
PE ( RR − 1)
1 + PE ( RR − 1)
With PE=6% and RR=3, AR=10.5%. If we consider that the accident occurred due to the
mobile phone use, this means that with this prevalence data, mobile phone use while driving
would explain about 10% of accidents.
This can also be calculated by using as a value for RR the risk associated with the owner of a
mobile phone, who can therefore potentially use it while driving, and the corresponding
prevalence, 44% (Chapelon and Sibbi, 2007). Taking RR=1.2, then AR=8.1%. In light of the
hypotheses made on the unobserved practice of hands-free telephoning for the first
estimation of attributable risk, the fact that this second estimation is of the same order of
magnitude is a very important element.
In conclusion, the estimation at 3 of the risk of an accident associated with using the mobile
phone while driving seems rather consistent in light of the results of epidemiological studies
and also experimental results. It can also be thought that this risk is relatively independent of
Collective Expert Report
- 83 -
13/12/2011
study populations. The prevalence of the exposure to telephoning while driving is on the
other hand more fluctuating over time and depends on the populations observed. As shown
in the calculation hereinabove, this prevalence value is determinant in estimating the
number of accidents or victims that can be associated with the practice of telephoning while
driving.
BIBLIOGRAPHY
BACKER-GRONDAHL A, SAGBERG F. Driving and telephoning; relative accident risk when using
hand-held and hands-free mobile phones. Safety Science 2011, 49: 324-330
BRACE C, YOUNG K, REGAN M. Analysis of the literature: the use of mobiles phones while driving.
Vagverket, Monash University, Accident Research Centre, 2007, 35
BRAVER ER, LUND AK, MCCARTT AT. Hands-free embedded cell phones and airbag-deployment
crash rates. Risk Anal 2009, 29: 1069, author reply 1070-1
CAIRD J, SCIALFA C, GEOFFREY H, SMILEY A. Effects of cellular mobile phones on driving
behaviour and crash risk: results of meta-analysis. CAA Foundation for traffic safety, University of
Calgary, 2004, 39p
CHAPELON J, SIBI P. Le téléphone portable au volant. Observatoire national interministériel de
sécurité routière. Report 28 March 2007
GIBSON JE, HUBBARD RB, SMITH CJ, TATA LJ, BRITTON JR, FOGARTY AW. Use of self-controlled
analytical techniques to assess the association between use of prescription medications and the risk of
motor vehicle crashes. Am J Epidemiol 2009, 169: 761-768
GREENLAND S. The effect of misclassification in matched-pair case-control studies. Am J Epidemiol
1982, 116: 402-406
GREENLAND S, KLEINBAUM D. Correcting for misclassification in two-way tables and matchedpair studies. Int J Epidemiology 1983, 12: 93-97
GRENDER JM, JOHNSON WD. Analysis of crossover designs with multivariate response. Stat Med
1993, 12: 69-89
GUO F, KLAUER S, HANKEY J, DINGUS T. Near crashes as crash surrogate for naturalistic driving
studies. Transportation Research Record 2010, 2147: 66-74
HICKMAN JS, HANOWSKI RJ, BOCANEGRA J. Distraction in commercial trucks and buses:
assessing prevalence and risk in conjunction with crashes and near-crashes. US department of
Transportation, Federal Motor Carrier safety Administration, Report, Sep. 2010
INSPQ. Avis de santé publique sur les effets du cellulaire au volant et recommandations. Institut
National de santé publique du Québec, 2007, 85p
KLAUER S, DINGUS V, NEALE J, SUDWEEKS JD, RAMSEY DJ. The impact of driver inattention on
near-crash/crash risk: an analysis using the 100 car naturalistic driving study data. NHTSA, National
Technical Information Service, Virginia, 2006, 182p
LABERGE-NADEAU C, MAAG U, BELLAVANCE F, LAPIERRE SD, DESJARDINS D. Wireless
mobile phones and the risk of road crashes. Accid Anal Prev 2003, 35: 649-660
LABERGE-NADEAU C, BELLAVANCE F, ANGERS J, MAAG U, et coll. Crash risk and cell phone
use: Important questions on the real risk for legal decision makers. Valdor Conference, Stockholm,
2006, 305-314
LENGUERRAND E, MARTIN JL, MOSKAL A, GADEGBEKU B, LAUMON B. Limits of the quasiinduced exposure method when compared with the standard case-control design. Application to the
estimation of risks associated with driving under the influence of cannabis or alcohol. Accid Anal Prev
2008, 40(3): 861-868
MARSHALL RJ, JACKSON RT. Analysis of case-crossover designs. Stat Med 1993, 12: 2333-2341
Collective Expert Report
- 84 -
13/12/2011
MCCARTT A, HELLINGA L, BRATIMAN K. Cell phones and driving: review of research. Traffic Inj
Prev 2006, 7: 89-106
MCEVOY S, STEVENSON M, MCCARTT A, WOODWARD M, HAWORTH C, et coll. Role of mobile
phones in motor vehicle crashes resulting in hospital attendance: a case-crossover study. BMJ 2005,
331: 428
NABI H, SALMI R, LAFONT S, CHIRON M, ZINS M, LAGARDE E. Attitudes associated with
behavioral predictors of serious road traffic crashes: results from the GAZEL cohort. Injury Prevention
2007, 13: 26-31
OLSON R, HANOWSKI R, HICKMAN J, BOCANEGRA J. Driver distraction in commercial vehicle
operations. US DoT, Federal Motor Carrier Safety Administration, 2009, 49p
ONISR. La sécurité routière en France, bilan de l’année 2007. La Documentation Française, Paris, 2008
REDELMEIER D, TIBSHIRANI R. Association between cellular-mobile phone calls and motor vehicle
collisions. N Engl J Med 1997a, 336: 453-458
REDELMEIER D, TIBSHIRANI R. Interpretation and bias in case-crossover studies. J Clin Epidemiol
1997b, 50: 1281-1287
REDELMEIER D, TIBSHIRANI R. Is using a car phone like driving drunk? Chance 1997c, 5-9
REDELMEIER D, TIBSHIRANI R. Car phones and car crashes: some popular misconceptions. CMAJ
2001, 164: 1581-1582
REDELMEIER D, TIBSHIRANI R, EVANS L. Traffic-law enforcement and risk of death from motorvehicle crashes: case-crossover study. Lancet 2003, 361: 2177-2182
ROBERTS I, MARSHALL R, LEE-JOE T. The urban traffic environment and the risk of child
pedestrian injury: a case-crossover approach. Epidemiology 1995, 6: 169-171
SAGBERG F. Accident risk of car drivers during mobile mobile phone use. Int J Vehicle Design 2001, 26:
57-69
SAYER J, DEVONSHIRE J, FLANNAGAN C. The effects of secondary tasks on naturalistic driving
performance. UMTRI, University of Michigan, 2005, 48p
SCHOUTEN H, KESTER A. A simple analysis of a simple crossover trial with a dichotomous outcome
measure. Stat Med 2009, 29: 193-198
STAMATIADIS N, DEACON JA. Quasi-induced exposure: methodology and insight. Accid Anal Prev
1997, 29: 37-52
SULLMAN M, BAAS P. Mobile phone use amongst New Zealand drivers. Transportation Research Part
F: Traffic Psychology and Behaviour 2004, 7: 95-105
TIBSHIRANI R, REDELMEIER D. Cellular mobile phones and motor-vehicle collisions; some
variations on matched-pairs analysis. The Canadian Journal of Statistics 1997, 25: 581-591
VIOLENTI JM. Cellular phone and fatal traffic collisions. Accid Anal Prev 1998, 30: 519-524
VIOLENTI JM, MARSHALL JR. Cellular phones and traffic accidents: An epidemiological approach.
Accident Analysis and Prevention 1996, 28: 265-270
WILSON J, FANG M, WIGGINS S, COOPER P. Collision and violation involvement of drivers who
use cellular mobile phones. Traffic Inj Prev 2003, 4: 45-52
YOUNG RA, SCHREINER C. Real-world personal conversations using a hands-free embedded
wireless device while driving: effect on airbag-deployment crash rates. Risk Anal 2009, 29: 187-204
Collective Expert Report
- 85 -
13/12/2011
Collective Expert Report
- 86 -
13/12/2011
6
Drivers’ perception of the risk linked to phoning while
driving
As the previous chapters in this document have identified, the results of experimental
studies and epidemiological studies converge and show that phoning while driving can
increase the risk of an accident, regardless of whether the phone is held in the hand or is
hands-free. The driver’s abilities to select and process the relevant information coming from
the road environment, to correctly evaluate the current situation and how it is changing as
well as his/her abilities to react in time and in a manner that is appropriate to the
requirements of the situation are altered. In France, nearly 9% of personal injury and damage
accidents are linked to phoning while driving.
Although the risk taken by phoning while driving has been identified by researchers, how is
this risk perceived by drivers? How do drivers evaluate the importance of the risk taken
when phoning while driving? Does this perception of the risk vary according to how the
mobile phone is used while driving? How is this risk judged in relation to all of the risks as a
whole linked to mobile telephony? How is this risk characterized? To what degree can the
perception of the risk taken encourage drivers to adjust their use of the phone while driving?
Evaluation of the importance of the risk taken by phoning while driving by
drivers
Several authors have taken an interest in what perception drivers have of the risk associated
with using the mobile phone while driving. This is how the act of phoning while driving
(whether or not with a hands-free phone) was compared, within the framework of the
European Sartre survey, to a series of other possible causes of road accidents (Vanlaar and
Yannis, 2006). This survey aimed to study the reported attitudes and behaviours of European
drivers in terms of risks on the road. It was carried out in 23 European countries from
September 2002 to April 2003. In sum, more than 24,000 drivers were surveyed. Fifteen
driving situations linked to the state of the driver, the state of the vehicle or the traffic
conditions were proposed to the people surveyed who had to estimate with what frequency
each situation was the cause of accidents. The drivers felt that phoning while driving,
whether or not held in the hand, was a driver’s behaviour having a low risk for an accident,
while showing strong prevalence in the case of the hand-held phone. Comparatively, driving
after consuming alcohol or drugs and driving with defective steering or brakes, or bald tires
were deemed as having a high risk for an accident with a strong prevalence for the first
series of situations and low for the second series.
The risk linked to phoning while driving was also compared to the risks generated by
various activities that drivers can be led to perform while driving.
In 2003, McEvoy et al. (2006) carried out a survey via a questionnaire on the distraction of
drivers with 1,347 Australian drivers. The drivers questioned had to estimate to what degree
certain behaviours while driving would increase the risk of an accident (table 6.I).
Collective Expert Report
- 87 -
13/12/2011
Writing and sending an SMS, driving with a blood alcohol concentration of 0.8 g/l, reaching
for an object on the rear seat of the car, reading a map and using a hand-held phone were
judged by more than 70% of drivers as strongly increasing the risk of an accident. Young
drivers (between the age of 18 and 30) on the overall evaluated the situations of distraction as
less risky that older drivers although they declared that they were more often engaged in
secondary tasks while driving.
Table 6.I: Drivers’ perception of the increase in crash risk conferred by various distracting and
other risk behaviours (according to McEvoy et al., 2006) (N=1,347)
Risk taken habit
Number
(N)
No
increase
small
increase
Moderate
increase
High
increase
Extreme
increase
Writing and sending a text message
1,314
0.3 (0.2)
1.8 (0.4)
9.7 (0.9)
33.7 (1.6)
54.5 (1.6)
Driving with a blood alcohol
concentration of 0.8 g/l
1,296
0.9 (0.3)
3.6 (0.6)
13.4 (1.1)
34.0 (1.6)
48.1 (1.6)
Reaching for object on backseat
1,339
0.5 (0.2)
4.2 (0.7)
17.4 (1.2)
42.4 (1.6)
35.5 (1.5)
Reading a map
1,339
1.0 (0.4)
4.1 (0.6)
25.4 (1.4)
43.6 (1.6)
25.9 (1.4)
Hand-held mobile phone use
1,326
1.5 (0.4)
7.0 (0.8)
21.6 (1.3)
38.2 (1.6)
31.7 (1.5)
Driving 80 km/h in a 60 km/h zone
1,332
3.5 (0.6)
8.8 (0.9)
30.4 (1.5)
38.8 (1.6)
18.5 (1.2)
Driving with a blood alcohol
concentration of 0.5 g/l
1,293
5.0 (0.7)
10.8 (1.0)
24.3 (1.4)
30.5 (1.5)
29.4 (1.5)
Daydreaming
1,337
5.3 (0.8)
20.3 (1.3)
38.1 (1.6)
27.2 (1.4)
9.1 (0.9)
Driving continuously for > 2hours
1,338
12.6 (1.0)
15.2 (1.1)
39.4 (1.6)
24.5 (1.4)
8.3 (0.9)
Observing scenery
1,344
12.4 (1.1)
26.6 (1.4)
44.0 (1.6)
14.7 (1.1)
2.3 (0.5)
Hands-free mobile phone use
1,311
14.7 (1.2)
30.0 (1.5)
39.6 (1.6)
11.2 (1.0)
4.4 (0.7)
Talking to passengers
1,344
30.7 (1.5)
38.7 (1.6)
27.6 (1.5)
2.3 (0.5)
0.7 (0.3)
The figures provided correspond to the weighted percentage by row; standard error is given in parentheses.
These results are confirmed by the survey on the use by drivers of new technologies, carried
out in nine countries (Australia, Austria, Spain, Finland, France, Netherlands, Portugal,
Czech Republic and United Kingdom) by the European Interaction project 9 . In sum, 7,677
people responded to this internet survey. One of the questions in the survey relates to the
degree of dangerousness of 23 actions that can be performed while driving and which can
distract the driver from the driving task (Britschgi et al., 2010). The situations for distraction
studied were linked to mobile phone use, using technologies pertaining to entertainment or
driving, the presence of passengers, the outside environment and reading/writing and being
lost in one's thoughts (table 6.II).
9
www.interaction-fp7.eu
Collective Expert Report
- 88 -
13/12/2011
Table 6.II: Sources of distraction studied in the European Interaction project
Mobile phone use
Use of technologies for the purposes of entertainment
Dialling a phone number
Answering a phone call
Talking on a hand-held mobile phone
Talking on a hands-free mobile phone
Writing an SMS
Reading an SMS
Listening to the radio, a CD, a tape or any other music
media
Listening to an audio book
Manipulating the radio or CD player controls
Manipulating the controls of a portable music player
(iPod, for example)
Using technologies pertaining to driving
Presence of passengers
Manipulating vehicle controls (air conditioning, rearview mirrors)
Looking at the navigation display
Manipulating the navigation system controls
Manipulating the settings of cruise control, speed limiter
or speed alert
Talking to passengers
Arguing with passengers
Interacting with children
Driving while a passenger in the rear is watching a film
Outside environment
Other distractions
Looking at a static advertising billboard
Looking at a scrolling advertising billboard or an
advertising screen with videos
Reading a note
Writing a note
Daydreaming / being lost in one's thoughts
Writing a note or an SMS and reading a note were deemed as extremely dangerous activities
by about 60% of the drivers, followed by reading an SMS (48%), being lost in one's thoughts
(44%) and phoning with a hand-held phone if it entails dialling the number (43%) or
conversing (38%). The drivers also identified as being a risk answering the phone (27%),
regarding dynamic advertising billboards (24%), arguing with passengers (22%)
manipulating a music player (19%) or a navigation system (18%), looking at static
advertising billboards (16%) and interacting with children (15%). The other actions were
deemed by less than 10% of the people questioned as extremely dangerous. It is therefore
actions that require long visual-manual control, such as writing and reading a note or an
SMS, that were identified as being the most dangerous by the people surveyed. Actions
generating a high cognitive or emotional load were also identified as having a risk for an
accident, but to a lesser degree.
Systematically, phoning with a hands-free phone is deemed as an activity carrying much less
risk than manipulating the keyboard of the mobile phone, taking the line and conversing
with a hand-held phone (Wogalter and Mayhorn, 2005; McEvoy et al., 2006; Britschgi et al.,
2010). The fact that phoning with a hands-free phone is not banned in the majority of the
countries is certainly at the source of this under-evaluation of the risk.
As such, if distractions induced by visual-manual interactions are deemed as the most at risk,
cognitive distraction linked to mobile phone conversation is under-estimated. This
observation is confirmed when the drivers are questioned about the various actions that they
can perform with their cell phone. Writing or reading an SMS, dialling a number,
manipulating the keyboard or reading the screen are actions deemed the most at risk
(Brusque and Alauzet, 2006; McEvoy et al., 2006; Britschgi et al., 2010).
Perception of the risk according to phone use while driving
Perception of the risk linked to mobile phone use while driving varies according to the habit
or not of phoning while driving, with non-users judging that the level of risk is higher than
Collective Expert Report
- 89 -
13/12/2011
users. Wogalter and Mayhorn (2005) have as such shown that among the drivers, those who
declare that they are not users of mobile phones, are more convinced that phoning while
driving negatively affects driving performance and that speaking on the phone can
potentially be at the origin of an accident. They are also more in favour of legislation banning
phone use while driving or limiting it to emergency calls.
The awareness of the risk taken when phoning while driving also differs according to the
uses that the drivers have for the mobile phone while driving. Sullman and Baas (2004) and
Hallett et al. (2011) have identified a negative correlation between the frequency with which
drivers use their mobile phone while driving and the perception that the latter have of the
dangerous nature of this practice. That is to say that the more the drivers use their phone
while driving, the less they feel it is dangerous.
The analysis of mobile phone practices while driving cannot be limited to a simple analysis
of the frequencies of use. Attention must also be given to possible self-regulation behaviours
initiated by the drivers (incoming calls only, taking the driving context into account when
deciding whether or not to initiate a conversation). Brusque and Alauzet (2006) have as such
identified four major groups of users: non-users, careful users, slightly disciplined users and
thoughtless users. The first three groups are of equivalent size (respectively 32%, 37% and 27%
of the people surveyed) while the latter group, thoughtless users, represents only a small
proportion of the sample (4%). In terms of perceiving the risk of an accident, the "non-users"
feel that the risk taken is very high (for 83% of them), thoughtless users are only 17% to find it
very important. The two other groups of users have intermediary judgments: 76% of the
careful users feel that the risk is high compared to 40% of the slightly disciplined users. And
yet, the more they phone while driving, the more they declare that they have already faced
hazardous situations when phoning while driving (Pöysti et al., 2005; Brusque and Alauzet,
2006). The most-commonly mentioned critical situations are: moments of inattention when
following a vehicle, trajectory deviations, not perceiving traffic signs and dropping the speed
to the point of disturbing other drivers (Lamble et al., 2002).
The population of drivers using a hands-free kit is rather specific. These are drivers that have
a high frequency of phone use while driving. They have a perception of the risk taken when
phoning while driving that is higher than drivers that are not equipped, which could explain
their choice of installing a hands-free kit in order to continue their practice with a degree of
safety that they feel is at a maximum and without the risk of a fine (Sullman and Bass, 2004).
By analyzing the effects of the Finnish law of 2003 banning the use of hand-held phones
while driving, Rajalin et al. (2005) showed that it was occasional users of mobile phones
while driving who for the most part decided to stop phoning while driving following this
ban, and the more frequent users decided to install a hands-free kit, and drivers with an
intermediary frequency of use continue to use their hand-held phone.
Perception of the road accident risk in relation to all of the risks linked to
mobile telephony
Martha et al. (2006) studied the representation in the media of the risks linked to cell phones,
whether pertaining to "social" risks concerning noise and incivilities, physical risks that are
inherent with the electromagnetic waves emitted by cell phones and relay antennas and the
risk of road accident linked to the use of the phone while driving a vehicle. The risks linked
to electromagnetic waves have captured the attention of journalists, well before the risks of
road accidents, in a ratio of 3 to 1 out of 120 articles published in the 3 French main
newspapers: Le Monde, Le Figaro and Libération from 1995 to 2002 and analyzed by the
Collective Expert Report
- 90 -
13/12/2011
authors. Among all of the risks linked to mobile telephony, that linked to phone use while
driving appears to be a danger that is freely accepted and individually controllable, while
that linked to the exposure to electromagnetic waves emitted by the relay antennas appears
as a danger, i.e. a danger that is not chosen and that is out of the individual's control. The
emissions of cell phones generate less fear than those of the relay antennas which remain less
important however. The authors explain this difference by the fact that in the case of the cell
phone, this entails a private use, which is chosen and which produces a direct individual
advantage, in opposition to the relay antennas which are dedicated for collective use, of
which we are subjected to, and of which the utility is not immediately perceived. In sum, we
can say that the risk of an accident linked to phone use while driving, is a risk that drivers
are familiar with and choose to take as they draw an advantage from it and they feel they can
control it.
White et al. (2004) took an interest in the perceived risk of hand-held cell phone use while
driving, and more particularly its characteristics in terms of detectability, probability,
severity, equitability and immediacy. Their results are based on a survey carried out in 2001
over 13,200 British people. The latter judged the risk as severe (the effects of phoning on
driving are not considered to be negligible), inequitable (those who phone while driving are
not a risk just to themselves) and probable (those surveyed would need little convincing that
phoning while driving was dangerous). Those questioned were for the most part, convinced
that the risk persists after the telephone communication stops (the effects are not only
immediate but can be delayed over time). This opinion supposes a certain awareness of the
emotional or cognitive load that can be generated by a phone conversation and which does
not cease once the conversation is over. The last characteristic of the risk studied was its
detectability, i.e. the facility with which a driver can detect whether or not his/her driving is
altered when he is phoning. The persons questioned had widely different opinions on this
point; some confirm the assertion and others refute it, which has not made it possible to
characterize the risk of phoning while driving in terms of detectability.
Several authors have identified an "optimism bias" in terms of the perception of the risk of
accidents linked to phone use while driving (White et al., 2004; Wogalter and Mayhorn,
2005). The risk of an accident is deemed higher for others than for oneself. This bias
corresponds to a systematic error in the perception that an individual has on what can
happen personally to him in comparison to what can happen to his/her peers. In the case of
a positive event, an individual will feel that this has a greater chance of happening to him
that to his/her peers and inversely in the case of a negative event, the latter has more chance
of happening to his/her peers than to him. This perception bias has been identified in
different fields, in particular in the field of health. This is even greater when the risk in
question can be considered as able to be controlled by the individual (Klein and HelwegLarsen, 2002) and if there are stereotypes for population groups that are most concerned by
this risk (Weinstein, 1980). This optimism bias has also been shown for risks linked to
electromagnetic waves emitted by cell phones and relay antennas (White et al., 2007). The
impression that it is easier to control exposure to the waves emitted by cell phones than by
relay antennas generates an optimism bias that is higher for the risk induced by cell phones
than by relay antennas. White et al. (2007) have also identified a utility bias: the utility of the
cell phone is deemed higher for oneself than for others. The optimism and utility bias are
respectively modulated downwards and upwards by the frequency of phone use.
Collective Expert Report
- 91 -
13/12/2011
Perception of the risk and regulation of phone use while driving by the
drivers
Recent research works have addressed the factors that explain driver intention on whether or
not to initiate the use of a mobile phone while driving. White et al. (2010) used the intention
model proposed by Ajzen's theory of planned behaviour (1991) as a theoretical framework.
According to this theory, any behaviour which requires a certain degree of planning can be
predicted by the intention of having this behaviour, with the intention being the result of
three factors: attitudes towards behaviour, associated subjective norms and perceived
behavioural control.
Attitudes towards behaviour designate the favourable or unfavourable opinions that a
person has of a studied behaviour. The subjective norms describe the perception that the
individual has of the social pressure exerted by those around them, their family, or friends so
that they adopt this behaviour. The perceived behavioural control corresponds to the facility
or difficulty perceived in whether or not to adopt this behaviour. Attitudes towards
behaviour, associated subjective norms and perceived behavioural control are determined by
underlying behavioural, normative and control beliefs, respectively.
In order to study the intentions of drivers to phone while driving, White et al. (2010)
surveyed, in 2006, 796 Australian drivers by asking them:
•
How likely is it that your using a mobile phone while driving in the next week would
result in the following: use time effectively, be distracted, be involved in an accident,
receive information, receive assistance in an emergency and be caught and ticketed
by the police?
•
How likely is it that the following people or groups of people would approve of your
using a mobile phone while driving in the next week: friends, family, companion,
work colleagues, other drivers and police?
•
How likely are the following factors to prevent you from using a mobile phone while
driving in the next week: the risk of getting a ticket, the demands of driving
conditions, the risk of an accident, the presence of police, the lack of a hands-free kit
and the intensity of the traffic?
The drivers were also asked about their frequency of phone use while driving and on their
use of a hand-held phone or a hands-free one.
Frequent users and occasional users of mobile phones while driving differ in terms of
behavioural, normative and control beliefs (table 6.III). These differences vary according to
the type of phone, suggesting that the factors at the origin of the intention to phone while
driving are not the same for hand-held phones and hands-free phones.
For hands-free phone users, it is the advantage afforded by the phone in terms of optimizing
time, social pressure (from friends, family and work colleagues) as well as a lesser perception
of the barriers to phone use while driving (driving context, risk of an accident and presence
of the police), that allow frequent users and occasional users to be differentiated. The risk of
getting a ticket and the presence of the police are mentioned as factors that influence the
intention to phone while driving. This leads one to assume that drivers do not have an
exclusive use of their hands-free kit or that they exchange text messages while driving.
Finally, the risk of an accident is not deemed as a possible consequence of phoning while
Collective Expert Report
- 92 -
13/12/2011
driving, it can be supposed that because it is allowed, phoning with a hands-free kit is not
deemed as dangerous.
For users of hand-held phones, optimizing travel time and keeping informed are the two
advantages afforded by the phone which justify frequent us of it while driving. Although
frequent users are aware of the risk that is taken in terms of distraction and tickets, this
awareness of the risk is not enough to counterbalance the advantages that are afforded.
Finally, although social pressure from the environment is less marked for users of hand-held
phones than for users of hands-free phones, it is greater for frequent users than for
occasional users of hand-held phones. Occasional users are more sensitive to the disapproval
of other drivers and of the police. Frequent users are on the overall less aware than
occasional users of the barriers to using the phone while driving. For both types of users, the
presence of the police and the demands of the road situation are two factors considered as
likely to limit phone use while driving.
Table 6.III: Mean values for beliefs of drivers according to handset type and frequency of use
(daily or more versus less than daily) (according to White et al., 2010)
Hands-free phone
Hand-held phone
Scale used: from 1 for extremely
unlikely to 7 for extremely likely
Frequent
use
Infrequent
use
Behavioural beliefs
n=145
n=36
Significativity
of the
difference
Frequent
use
Infrequent
use
n=288
n=270
Significativity
of the
difference
How likely is it that your using a mobile phone while driving in the next week would result in the following?
Using time effectively
5.37
3.31
0.000
4.56
2.36
0.000
Being distracted from driving
3.73
3.53
0.581
4.50
3.68
0.000
Being involved in a crash
2.46
3.08
0.060
3.49
3.17
0.075
Receiving information (e.g., directions,
important news)
4.12
3.22
0.023
4.34
2.75
0.000
Receiving assistance in an emergency
3.28
3.33
0.890
3.48
3.28
0.248
Being caught and fined by the police
2.07
2.58
0.121
3.63
2.98
0.000
Normative beliefs
n=145
n=34
n=288
n=270
How likely is it that the following people or groups of people would approve of your using a mobile phone while driving in the next
week?
Friends
4.50
3.35
0.006
3.98
2.33
0.000
Family members
4.37
3.06
0.002
3.26
1.99
0.000
Partner/boyfriend/girlfriend
4.34
3.24
0.009
3.67
2.11
0.000
Work colleagues
4.77
3.26
0.000
3.95
2.29
0.000
Other drivers
3.78
3.18
0.128
3.24
1.94
0.000
Police
2.99
2.62
0.371
2.21
1.58
0.000
Control beliefs
n=146
n=34
n=285
n=274
How likely are the following factors to prevent you from using a mobile phone while driving in the next week?
Risk of fines
3.90
5.71
0.000
4.46
5.38
0.000
Demanding driving conditions (e.g.,
weather, changing lanes)
4.90
6.06
0.005
5.42
5.82
0.018
Risk of an accident
4.74
5.91
0.005
5.06
5.80
0.000
Police presence
4.53
5.88
0.002
5.76
5.75
0.954
Lack of hands-free kit
5.08
5.24
0.735
3.91
5.06
0.000
Heavy traffic
4.31
5.47
0.006
4.67
5.47
0.000
Collective Expert Report
- 93 -
13/12/2011
Walsh et al. (2008) have also used Ajzen's theory of planned behaviour in order to explain
the intention of drivers to use their cell phone while driving according on the one hand, to
attitudes, subjective norms and perceived behavioural control of the driver and on the other
hand, to his/her perception of the risk of an accident and ticketing by the police. The
intention to call and text message was studied for four driving scenarios (according to the
speed of the car and of the time pressure that the driver is subjected to).
The intention to phone while driving can be explained by the youthfulness of the driver, the
professional use of the car, the beliefs on the advantages procured by phoning while driving
and the social pressure that the driver is subjected to by his/her environment. It is the
favourable attitude towards phoning while driving that has the greatest explanatory power
of the intention to phone.
The results obtained on the intention to call and text message differ according to the scenario
considered. It is therefore impossible to propose intention predictors that are valid for the
different scenarios. It can nevertheless by noted that the professional use of the vehicle
predicts the intention for calling but not that for text messaging, as SMS remain a practice of
a private nature. Social pressure contributes in explaining the intention to call in scenarios
that include time pressure with a concern for reassuring one's family, friends, work
colleagues, etc. The risk of getting a ticket from the police for drivers text messaging is
known but does not limit their intention of text messaging while driving.
The population of young drivers has received special attention as this is the population
bracket that is most often equipped with cell phones as well as the one that declares, in the
vast majority, that it phones or exchanges text messages while driving (Nelson et al., 2009;
Atchley et al., 2011). Nelson et al. (2009) have taken an interest in a population of students at
the University of Kansas and have studied to what degree the perception of the risk taken
when phoning while driving and the importance perceived of the call affected the driver's
intention to initiate a call or to answer a call while driving. This work showed that the risk
perceived had a negative effect on the driver's intention to phone, but that the latter
remained limited. The effect is above all marked in the case of an incoming call, as if it was
easier for the driver to ignore the call. In the case with outgoing calls, it is the importance
that is perceived of the call that will be the best predictor of the driver's intention to initiate a
call. The authors have also identified that if the perceived risk could modulate the driver's
intention to phone, the effect would be too weak to affect the frequency of phone use while
driving.
The practices of the students at the University of Kansas in terms of exchanging text
messages while driving were also studied by distinguishing between reading, replying or
initiating an SMS (Atchley et al., 2011). The proportions of young drivers having these three
types of behaviour while driving are respectively equal to 92%, 81% and 70%. The persons
questioned are nevertheless perfectly aware of the risk taken when exchanging text messages
while driving and they even feel that this risk is much higher than that for phoning while
driving. Writing a text message, to reply an SMS or to initiate an SMS, is deemed a very
dangerous action. However, the risk perceived has a significant effect only on the intention
of the driver to initiate an SMS. In the case of the driver's intention to answer an SMS, no
effect was identified although the distractive task is comparable, as if the social pressure to
remain in contact with their peers was more important that the perception of the risk taken.
The importance of the peers and the social norms associated with belonging to the group
was demonstrated by Nemme and White (2010) who aimed to predict the intention and the
behaviour of young Australian drivers with regards to writing and reading text messages
while driving using various psychosocial factors. Indeed, the more a person is convinced that
his/her peers approve of exchanging text messages while driving and that they themselves
Collective Expert Report
- 94 -
13/12/2011
exchange text messages while driving, the higher will be their intention to reproduce this
behaviour. The beliefs of the young driver on the attitudes and behaviours of his/her peers
have an influence on his/her intention but also on his/her behaviour in terms of writing and
reading text messages while driving.
The results of these researches aiming to better understand the determinants in the intention
of mobile phone use while driving are important if it is desired to set up regular public
awareness campaigns that are better targeted.
In conclusion, drivers poorly assess the risk that they are taking by phoning while driving.
Although the visual-manual distraction generated by writing or reading an SMS is well
perceived, this is not the case for the cognitive distraction generated by phone conversation.
The usage of a hands-free kit while driving is deemed as an activity with much less risk than
using a hand-held phone.
The perception of the risk linked to phone use while driving varies according to the uses that
the drivers have of the cell phone while driving:
•
drivers that do not use the phone while driving deem that the risk is higher than
those who phone while driving;
•
drivers who phone while driving the most frequently and systematically find the risk
to be lower than occasional drivers;
•
drivers who use a hands-free kit find it higher than drivers who are not equipped,
which can be at the origin of their choice to install a hands-free kit.
The risk linked to phone use while driving appears as a familiar risk that is freely taken as it
produces advantages and it seems to be easily controllable. Drivers consider that the risk of
an accident is greater for other drivers than for themselves.
Although the perception of the risk of accidents and ticketing does exist for most drivers, it is
not however enough to counterbalance the advantages afforded by the cell phone and the
social pressure from those around who encourage its use while driving.
Better knowledge of the factors that influence the driver's intention whether or not to initiate
cell phone use while driving seems to be an interesting path in order to better target future
regular public awareness campaigns concerning the risk of phoning while driving.
REFERENCES
AJZEN I. The theory of planned behavior. Organizational Behavior and Human Decision Processes 1991,
50: 179-211
ATCHLEY P, ATWOOD S, BOULTON A. The choice to text and drive in younger drivers: Behavior
may shape attitude. Accident Analysis and Prevention 2011, 43 (1): 134-142
BRITSCHGI V, RÄMÄ P, PENTTINEN M. Survey on individual and cross-cultural differences in the
use of In-Vehicle Technologies (IVT): Results and analysis of the Internet survey. Report FP7 Project
Interaction, 2010, 118p
BRUSQUE C, ALAUZET A. L’utilisation du téléphone mobile au volant en France: entre déni du
risque et autorégulation du comportement. Recherche Transports Sécurité 2006, 91: 75-97
HALLETT C, LAMBERT A, REGAN MA. Cell phone conversing while driving in New Zealand:
Prevalence, risk perception and legislation. Accident Analysis and Prevention 2011, 43(3): 862-869
KLEIN CTF, HELWEG-LARSEN M. Perceived Control and the Optimistic Bias: a Meta-Analytic
Review. Psychology and Health 2002, 17: 437-446
Collective Expert Report
- 95 -
13/12/2011
LAMBLE D, RAJALIN S, SUMMALA H. Mobile phone use while driving: public opinions on
restrictions. Transportation 2002, 29: 223-236
MARTHA C, COULON M, SOUVILLE M, GRIFFET J. Les risques liés à l’usage du téléphone portable
et leur représentation médiatique: l’exemple de trois quotidiens français. Santé Publique 2006, 2: 275288
MCEVOY SP, STEVENSON MR, WOODWARD M. The impact of driver distraction on road safety:
results from a representative survey in two Australian states. Injury Prevention 2006, 12: 242-247
NELSON E, ATCHLEY P, LITTLE TD. The effects of perception of risk and importance of answering
and initiating a cellular phone call while driving. Accident Analysis and Prevention 2009, 41(3): 438-444
NEMME HE, WHITE KM. Texting while driving: Psychosocial influences on young people’s texting
intentions and behaviour. Accident Analysis and Prevention 2010, 42(4): 1257-1265
PÖYSTI L, RAJALIN S, SUMMALA H. Factors influencing the use of cellular (mobile) phone during
driving and hazards while using it. Accident Analysis and Prevention 2005, 37: 47-51
RAJALIN S, SUMMALA H, PÖYSTI L, ANTEROINEN P, PORTER B. In-Car Cell Phone Use and
Hazards Following Hands Free Legislation. Traffic Injury Prevention 2005, 6: 225-229
SULLMAN MJM, BAAS PH. Mobile phone use amongst New Zealand drivers. Transportation Research
Part F: Traffic Psychology and Behaviour 2004, 7: 95-105
VANLAAR W, YANNIS G. Perception of road accident causes. Accident Analysis and Prevention 2006,
38: 155-161
WALSH SP, WHITE KM, HYDE MK, WATSON B. Dialling and driving: Factors influencing intentions
to use a mobile phone while driving. Accident Analysis and Prevention 2008, 40: 1893-1900
WEINSTEIN ND. Unrealistic optimism about future life events. Journal of Personality and Social
Psychology 1980, 39: 806-820
WHITE KM, HYDE MK, WALSH SP, WATSON B. Mobile phone use while driving: An investigation
of the beliefs influencing drivers’ hands-free and hand-held mobile phone use. Transportation Research
Part F: Traffic Psychology and Behaviour 2010, 13: 9-20
WHITE MP, EISER JR, HARRIS PR. Risk perceptions of mobile phone use while driving. Risk analysis
2004, 24: 323-334
WHITE MP, EISER JR, HARRIS PR, PAHL S. Who Reaps the Benefits, Who Bears the Risks?
Comparative Optimism, Comparative Utility, and Regulatory Preferences for Mobile Phone
Technology. Risk Analysis 2007, 27(3): 741-753
WOGALTER MS, MAYHORN CB. Perceptions of driver distraction by cellular phone users and
nonusers. Human Factors 2005, 47: 455-467
Collective Expert Report
- 96 -
13/12/2011
7
From regulations to debate: government responses to
mobile phone use while driving
This chapter covers the "public policy responses (policy) concerning mobile phone use while
driving" (Hahn and Dudley, 2002), such as presented in French and English language
literature. The latter includes little research from public policy sociologists and from political
scientists. The latter have very little interest or none at all in road safety policies. Des jurists,
economists, psychologists and engineers nevertheless incorporate this interrogation into
their questioning. They are interested in the "measures" adopted to respond to mobile phone
use while driving (Regan et al., 2009), i.e. the rules, government action programs developed,
as well as their implementation and how they are received. This research shows that most of
the responses involve the law. In France, for example, Order no. 2003-293 of March 31, 2003
creates Article R 412-6-1 of the Highway Code which banned "the use of a hand-held mobile
phone by the driver of a vehicle in circulation". Driving with a mobile phone in their hand, a
driver is, in France, risks a lump-sum fine of €35 (€22 is it is reduced, i.e. paid within 3 days)
and 2 points off their driving license. Measures of this type have been taken by almost all of
the governments of the European Union and by other countries with similar conditions of
life. But, existing literature also reminds that these are not the only measures that have been
decided or that can be considered. On the overall, the measures taken by governments raise
questions, because they are hardly evaluated and also because they remain highly focused
on controlling the driver's behavior (deviant).
Adopted and proposed measures
Recourse to law is a privileged solution in most countries. Solely taking regulatory and legal
measures into account is however too restrictive in order to characterize public action
intended to address the problem of telephoning while driving.
Recourse to law
Recourse to law is based on the hopes of modifying the driver's behavior. Two types of laws
exist. Laws of a general nature allow law enforcement officials to reprimand and sanction
driving that they feel is dangerous. The problem with mobile phone use while driving is then
treated within the framework of the general traffic rules and therefore regulations that
existed before the problem was identified. The case of France is, before 2003, exemplary in
this treatment. In accordance with Order no. 61-93 of January 21, 1961, "a vehicle driver must
constantly be in a state and in a position to suitably perform and without delay all of the
maneuvers that he is responsible for (…)". Yet, around the years 1990-2000, most
governments opted for specific regulations, i.e. explicitly treating mobile phone use while
driving. In 1999, Japan was the first country to ban the use of hand-held cell mobile phones
while driving, although the state of Victoria (Australia) banned the use in 1988. The vast
Collective Expert Report
- 97 -
13/12/2011
majority of States, and France is one of them, have as such opted for a total ban on mobile
phone use while driving but for a ban on hand-held mobile phones. Some cities, such as
New-Delhi, have banned all mobile phone use while driving.
Adopting banning laws, even partial bans, is firstly aimed at sending a message to drivers
indicating the risks taken by using a mobile phone while driving. However, adopting
"hands-free" laws is not without ambiguity, since it can suggest that using a hands-free kit
would sufficiently reduce the risks incurred. Finally, it introduces discrimination between
drivers who can or cannot equip themselves with a hands-free system. At the beginning of
the 2000's, "hands-free" laws were able however to appear as a politically "reasonable"
solution. Authors as such view these as laws of compromise, which takes into account a
relatively good reception of the banning measures, such as is indicated in the opinion
surveys, as well as a probable and rapid distribution of this communication instrument and
its use. This solution also allows for setting up educational measures concerning the dangers
of use and above all to not mobilize those who would feel that they had an interest, in
particular an economic one, in using this tool while driving (Lamble et al., 2002).
The main variants, from one country to another, therefore concern the sanction, i.e. the
amount of the fine and whether or not there are also penalty points taken off the driver's
license (table 7.I). The sanction can also vary over time, with the example of the stiffening of
the English text in 2007. Three penalty points are now at stake. A more precise analysis
further indicates that usage restrictions exist or are being considered, according to the type of
device, the duration of the call and even the location of use. Currently, bans targeted to
certain populations exist: these are very young drivers in 18 American states and the District
of Columbia (Foss et al., 2009). Exceptions to the general framework have been adopted. This
is the case for several professions: in the United States, it is banned for school bus drivers, for
example, to use any type of cell phone. Inversely, in Australia, police officers are exempt
from the ban on driving with a hand-held mobile phone. The emergency calls can also be
authorized, as can be called to parents for the youngest drivers. More recently, laws
prohibiting "texting" for all drivers (SMS messages). This is the case in the state of New York
which, since November 2009, has banned reading, writing and sending messages via a cell
phone while driving. In 2001, it was the first American state to ban hand-held mobile
phones.
The laws adopted to fight against the inherent risks with mobile phone use or other
communication tools while driving are therefore based on the use properly speaking, but
also on the age, for example, or the status of the driver-user of the telephony device.
Table 7.I: Existing regulations in the European Union 10
The 27 countries in the
European Union
Ban on hand-held mobile
phones
(or adoption of a "hands-free
law")
Date of the ban
Sanctions
Germany
YES
February 1, 2001
April 1, 2004
40 euro fine
+ 1 penalty point (18 resulting in the
revocation of the driving license)
Austria
YES
July 1, 1999
50 euro fine
Belgium
YES
July 1, 2000
100 euro fine
Bulgaria
YES
May 2002
Fine of about 25 euros + 6 penalty
points (39 resulting in the
10 For more details, refer to Janitzek et al., 2010 pages: 123-180
Collective Expert Report
- 98 -
13/12/2011
revocation of the driving license)
Cyprus
YES
June 25, 1999
85 euro fine + 2 penalty points (12
resulting in the revocation of the
driving license)
Denmark
YES
July 1, 1998
67 euro fine
Spain
YES
January 21, 2002
200 euro fine
Loss of 3 points off the driving
license (12 resulting in the
revocation of the driving license)
Modified in 2010
Estonia
YES
40 euro fine
Finland
YES
January 1, 2003
50 euro fine
France
YES
April 2003
Lump-sum fine: 35 euros
Loss of 2 points off the driving
license (out of 12)
Greece
YES
Minimum fine of 100 euros + 3
penalty points (25 au total)
Hungary
YES
38 euro fine (urban area at 75 euros
(highway) + 3 penalty points (18
resulting in the revocation of the
driving license)
Ireland
YES
Italy
YES
148 euro fine
5 penalty points (out of 20)
Latvia
YES
15 euro fine
September 1, 2006
60 euro fine
2 Penalty points (12 resulting in the
revocation of the driving license)
Lithuania
YES
April 1, 2003
Fine of about 5 to 11 euros
Luxembourg
YES
August 1, 2001
74 euro fine
Malta
YES
Netherlands
YES
23 euro fine
March 30, 2002
160 euro fine
Poland
YES
54 euro fine
Portugal
YES
Minimum fine of 120 euros
Czech Republic
YES
40 euro fines
3 penalty points (12 resulting in the
revocation of the driving license)
Romania
YES
Fine between 15 and 25 euros, 2
penalty points (out of 15)
United Kingdom
YES
December 2003
60 pound fine
3 penalty points (since February
2007) (12 resulting in the revocation
of the driving license)
Slovakia
YES
2009
33 to 250 euro fine
Slovenia
YES
Sweden
NO
120 euro fine
a
On June 11, 2008, the Swedish parliament voted against a draft law on banning (267 against 17 votes). On the one hand, the
parliament advances the fact that there is not enough research on the mobile phone and safety in the car. On the other hand, the
parliament is raising questions on the manner in which a law would be followed.
a
Yet, recourse to law cannot have for sole objective modifying the behavior of drivers.
Lawmakers can also address the other stakeholders involved in resolving the problem to be
fought and in particular to those of which the technological and commercial choices can have
an impact on mobile phone use while driving (Michael, 2005). A requirement as to
construction standards, for automobile firms and manufacturers of mobile telephony devices
can as such be considered or simply encouraging the design and integration into vehicles of
devices aimed at reducing the potential for distraction. Although recourse to new
Collective Expert Report
- 99 -
13/12/2011
technologies and improving ergonomics can offer solutions, a certain number of reports and
research fail to show a significant reduction in the risk due to the use of the most recent
technologies (Nikolaiev et al., 2010). More radically, other research recommends that
automobile manufacturers be subjected to standards aimed at restricting or in neutralizing
the use of telematic devices while driving (National Institute of Public Health of Quebec,
2006). But, it is without a doubt easier to formulate such a recommendation in Quebec than
in countries where there is a powerful automobile industry. Rather than legislative
injunctions, manufacturers prefer voluntary approaches, if only because regulations in this
field can become obsolete quickly (Regan et al., 2009).
Certain obligations can also be required of the professions that are the most concerned. With
regards to this, the main regulations adopted concern informing about the dangers of use.
Starting in 1987, an obligation to inform is, for example, required of car rental companies in
California (Hahn et al., 2000). Another widely used requirement is the systematic collection,
by law enforcement, of data on mobile phone use during an accident. This is, for example the
case, from 1991 on, in Minnesota. Ten years later, Hahn and Dudley (2002) feel that the
request for data on this problem is the most-widely adopted action program by the
American states, although many draft laws aimed at banning or restricting mobile phone use
have rarely been adopted by lawmakers. Without data making it possible to precisely and
systematically document mobile phone use among the causes of the accident, it is difficult to
assess the pertinence and the effectiveness of regulations on mobile phone use while driving,
which requires the most systematic collection possible of this information during the taking
of information or investigation of the accident. In addition to legal requirements,
governments are also trying to mobilize institutions which are in the best position to provide
this information. As such, in England, the government has tried to mobilize the main
association that represents the police forces, the ACPO (Association of Chief Police Officers)
(Tunbridge, 2001). However, the existing research insists, even today, on the still sporadic
nature of this work of documenting and proposing the use of black boxes, making it possible
to record mobile phone use at the time of the accident.
Other regulations further aim to increase awareness and further involve private
stakeholders. This entails encouraging, for example, initiatives from insurance companies
and employers in order to avoid or, if it is absolutely necessary, limit cell mobile phone use
by employees. English regulations, for example, require employers to do this, even if the
employees themselves have to preserve themselves from the risks inherent with driving
activity (Tearle, 2004). In France, on November 5, 2003, the Commission on Accidents in the
Workplace and professional diseases of the CNAMTS, bringing together representatives of
the main employee unions and employers, asked company heads and employees not to
mobile phone while driving, "regardless of the technical device". Not only do half of
industrial accidents take place on the road, but the new technologies have largely pushed
back and extended the conventional limits of the workplace (Dinkelacker, 2005). Although
the ability to communicate and exchange information, during travel, gives the feeling of
making the employee more effective and more productive, is also sharply increases the
causes of distraction for the worker when driving and the risks of an accident. These risks are
therefore taken into account by the management and labor partners, so that companies or
and branches develop policies on the use of the mobile phone while driving and that good
practices in this area are distributed and become generalized. But, of course, adopting a
company policy concerning mobile phone use while driving is not enough. The employer
must also be in a position to have it complied with. Pursuing such objectives is all the more
so pertinent as is the risk for an employer to have to deal with the law, in the event an
employee is involved in a road accident, cannot be fully excluded. The specific link created
Collective Expert Report
- 100 -
13/12/2011
by the labor contract is not interrupted, when the employee, within the framework of an
assignment set by the employer, drives a vehicle on the public way.
These various recourses to law do however raise the question of controlling it and the
effectiveness of the sanction in the event of non-compliance. The limits set by law do not
create sufficient conditions for improving road safety. This has to be accompanied by control
and non-compliance with the rules must effectively be sanctioned. Yet, one of the main
critiques made in extending the ban to hands-free kits resides, as for texting too, in the
difficulty for police officers to detect these practices, unless they are provided with
technological tools which allow for this or unless they can massively stop drivers. It would
be suitable, for example, to set up road barricades, such as what some countries do to fight
against alcohol while driving. Literature furthermore makes this impossible control one of
the reasons for which lawmakers at the beginning o the 2000's did not vote for a full ban
(Lamble et al., 2002). "Hands-free" laws however are also perceived as being difficult to
apply and in particular at night or for vehicles equipped with tinted windows. In the same
way, restrictions that apply to a particular age group can be particularly delicate to control
for law enforcement officials. For young drivers, research work concludes however that there
is relatively good compliance with the restrictions that apply to them (Foss et al., 2009). One
of the main keys in the effectiveness of a ban for this age group would reside within the
control exerted by parents. This indirect control does require however the development of
targeted communication campaigns in order to increase awareness of young people and
their parents as to the dangers that the latter incur when driving.
Existing studies judge that the risk, for a driver, to be caught with a mobile phone in hand is
extremely low. So, detecting violations of mobile phone use while driving remains a
challenge for law enforcement officials. In addition, their attitude, and likewise that of
judges, with regards to this violation is not univocal. They do not all attribute the same
degree of seriousness to the violation committed as such. Here, we find one of the traditional
debates in analyzing road safety policies, which was perfectly illustrated by recourse to the
automation of controlling and sanctioning violations to the authorized speed. Automation
has, on the one hand, made it possible to do away with the phenomenon of "indulgences"
with regards to excessive speeds in France and, on the other hand, has confirmed that a
change in behavior has more chance of being obtained, when the risk of receiving a sanction
is deemed to be high by the users. Once of the keys to the effectiveness of the legislation, and
particularly over the long term, resides in the intensity of the control, compliance with it and
in the advertizing concerning the intensity of this control.
Recourse to other instruments for public action
Other public actions, which do not pertain to sanctions and repression have been
implemented (Kalin, 2005; Nikolaiev et al., 2010). These can take the form of informative
work for drivers or other groups – employers – on the risk incurred in the case of mobile
phone use while driving. Major communication campaigns and also more targeted
campaigns have as such been implemented, for the least-experienced drivers, for example, or
in order to provide information about the inherent risks with a particular type of use (texting
today). We do not intend to develop this dimension here.
Educational efforts have also been developed (Kalin, 2005), in driver training programs,
however the distraction factor remains neglected (Regan et al., 2009). A certain number of
interested stakeholders – elected officials, road safety experts, automobile clubs – feel even so
Collective Expert Report
- 101 -
13/12/2011
that education offers a good approach in order to increase awareness in drivers of the risks
that they take when using a cell phone when driving (Nikolaiev, 2010).
Beyond the beliefs in the virtues, and in particular in the long term, of education, all
legislation is subject to debate, i.e. it comes up against opponents. The propositions for a ban
or restriction, accompanied with sanctions, for mobile phone use while driving do not escape
this. In the United States, for example, the difficulty in passing laws in the states that ban or
reduce mobile phone use while driving is accompanied by strong mobilization from the
main interest groups involved. This mobilization has taken either the form of financing for a
vast communications campaign (The Cellular Telecommunication & Internet Association), or
than or developing educational programs (American Automobile Association). These programs
made it possible to introduce the question of distraction into driver training (Kalin, 2005).
Regardless of the motivations, recourse to law is therefore not presented without an
alternative and without powerful support for measures that are alternative to the ban.
The American experience confirms the hypothesis of the compromise offered by "hands-free"
laws. On the one hand, public opinion seems to be rather favorable to usage restrictions due
to a risk that is well identified and rapidly advertized. This has encouraged governments to
take action. On the other hand, a full ban appears difficult to apply and can generate strong
opposition from the various stakeholders. However, the American case can appear to be
isolated, in particular due to the pressure that is traditionally exerted by interest groups on
lawmakers. The choice between various measures or strategies for action cannot be
considered, in all countries, as the momentary result of a power relationship between
competing groups of pressure. Measures can also be replaced over time. As such, the least
restrictive measures (data collection, developing communication campaigns) are in general
replaced with more restrictive measures (usage restriction).
The measures taken in France and in England since the end of the 1990's show rather well
this type of dynamics. For the English, adopting the "hands-free" law, in December 2003, fell
in line with a series of measures that have been implemented since 1995. Between 1995 and
1997, the number of accidents, for which mobile phone use while driving is considered to be
the main factor, is particularly low (Tunbridge, 2001). In the spring of 1998, the accidental
death of a rock star however contributed to the media's coverage of this new stake in road
safety. When Cozy Powell lost control of his Saab 900, near Bristol, he was on the mobile
phone with his companion. The investigation however established that he was also under
the influence of alcohol, driving at an excessive speed under pelting rain, and forgot to fasten
his seatbelt! A study of the Transport Research Laboratory (TRL), ordered by the Ministry of
Transportation (published in November 1998), gave special attention to whether or not the
mobile phone is held in the hand. During this same period, discussions between ministries,
with representatives of the cell mobile phone industry and with other stakeholders were
organized. Placing this on the political agenda, due to the mobilization of the media as well
as road safety experts, resulted in a campaign for increasing driver awareness, in March
1998, then by the distribution of an information brochure by the Ministry of Transportation,
carried out in collaboration with the association representing the operators and
manufacturers of cell mobile phones but also the ACPO and the Automobile Association. In
1999, recommendations on the use of cell mobile phones in relation to road safety were
incorporated into the new Highway Code and, in 2003, the banning law was adopted. In
France too, and during the same period, the campaigns for increasing driver awareness and
the expert reports preceded the inscription of the ban into law. In the middle of the 1990's,
INRETS researchers thus recommended "the mandatory installation of a hands-free system"
Collective Expert Report
- 102 -
13/12/2011
and felt that major de communication campaigns should be carried out (Pachiaudi et al.,
1996).
Finally, although the various measures that can be considered can be regarded as alternative
choices and, in a more dynamic optics, as successive options, it should be recalled that the
law, in order to be effective, must not only benefit from an effective control that it is
complied with by law enforcement, but also be supported by communication campaigns that
do not only inform about the dangers of mobile phone use while driving but also the risk of
a sanction in the event the law is not complied with. In sum, although it is possible to isolate
the various measures, for the purposes of the analysis, government action programs are
better off associating these.
Measures in question
Literature shows the doubt and questions as to the pertinence and the effectiveness of the
measures adopted, in particular, because they often appear "disconnected" from any
approach to analyzing and assessing public policy (Hahn and Dudley, 2002).
Old measures and for which the impact has hardly been assessed
The laws adopted are now old – some are nearly ten years old – with regards to the rapid
development of communications technologies and highly expanding usage in certain user
categories. Around the years 1990-2000, when the "hands-free" laws were designed and
adopted, few deaths could be attributed to mobile phone use while driving (Hahn et al.,
2000). In 2007, 16 American states published data on the number of automobile accidents, for
which the use of a hand-held mobile phone was considered to be a causal factor. This data,
which is contested, indicated that the use of a hand-held mobile phone was reported as a
factor in less than 1% of automobile accidents (Sundeen, 2007). However, and very early,
pioneer research had informed about the dangers of telephoning while driving (Pachiaudi,
2001; Pachiaudi et al., 1996). They did so more particularly using statistical studies on the
risks incurred (Redelmeier and Tibshirani, 1997).
Very early too, i.e. around the 2000's, the "hands-free" laws were denounced as contrary to
scientific results, which show that "hands-free" devices do not avoid the cognitive distraction
linked with conversation (Kalin, 2005). Better yet, some of these results indicate that
speaking with a "hands-free" mobile phone did not provide any significant advantages in
terms of safety in relation to a hand-held mobile phone (Redelmeier and Tibshirani, 1997;
Hahn and Dudley, 2002; MacCartt et al., 2006). Therefore, the safety procuring potential of
these laws is deemed limited and even incoherent in relation to scientific literature (INSPQ,
2006). Sometimes even, they were denounced as bearing perverse effects, since they were
sending an incorrect safety-procuring message to drivers (Kalin, 2005). This result led
authors (Kalin, 2005), but also institutions, such as CNAMTS to not draw a distinction
between the use of hand-held and non-hand-held mobile phones and others, such as the
INSP of Quebec, to recommend "a full ban on the use of cell mobile phones while driving
whether or not held in the hand". Authors, and in particular jurists, feel that a stringent
application of just the laws making it possible to sanction driving that is not cautious or
deemed as dangerous would be more effective than "hands-free" laws. They would be easier
for law enforcement officials to apply: whether a person is holding their mobile phone close
Collective Expert Report
- 103 -
13/12/2011
to their ear or whether they are combing their hair, their driving can be judged as imprudent
and as such be subject to a reminder of the law or possibly be sanctioned (Kalin, 2005).
Of course, for ten years now, literature on the subject has increased and the preliminary
knowledge on mobile phone use while driving has been supplemented. But, regardless of
the country and existing legislation, mobile phone use at the time of the accident is still
hardly documented in accident reports (McCartt et al., 2010). There is also little information
available on the effectiveness of the repression of the non-compliance with the regulations
adopted, such as on the acceptance of police action by the publics involved. More
fundamentally, the impact of the measures taken on the behaviors of users has hardly been
assessed (Brace et al., 2009). Yet, lacking an assessment of the behavioral changes generated
by existing laws, it is difficult to design any reorientation of public efforts based on
convincing data.
Some research does however attempt to document and measure the changes in behavior of
drivers before and after the adopting of "hands-free" legislation or targeted bans. They also
strive to follow the developments in behaviors over time. The main method used is that of
observations made over two or several periods, i.e. before and after the effective date of the
legislation as was done, for example, by O’Meara and his colleagues in Ireland (2008) and
Rajalin and his colleagues in Finland (2005). Research also strives to compare two
jurisdictions: one being provided with dedicated legislation and the other that was devoid of
this at the time of the survey. Another method, which moreover is often associated with the
first, consists in carrying out surveys or interviews with drivers and their family. This tool
makes it possible to grasp the public opinion with regards to the law as well as the attitudes
declared with regards to mobile phone use while driving. This makes it possible to
differentiate uses according to age groups or other socio-demographic characteristics
(McCartt et al., 2010).
The most mentioned assessment research in literature addressing the laws adopted in the
state of New-York, in 2001, and in Washington DC are those of Anne T. McCartt and her
colleagues. This research showed a substantial decrease in mobile phone use soon after the
effective date of the ban: a decline of about 50% in hand-held mobile phone use, with
however a return to the rate prior to the legislation after one year in New York (McCartt et
al., 2003; McCartt and Geary, 2004). A study carried out in Finland has similar results
(Rajalin et al., 2005). But, in Washington DC, the decline persisted nearly one year after the
law was adopted, which is explained by particularly strong controls as to compliance with
the new legislation (McCartt and Hellinga, 2007). In 2010, McCartt and her colleagues
evaluated the effects, long term ones this time, of the two legislations, to which they added
the legislation that was adopted in Connecticut in 2006. Over a long period, hand-held
mobile phone use remains lower than it would be if a law had not been adopted. But the
extent of the reduction observed varies from one state to another. The explanation initially
put forth of a control in the application of the law by the law enforcement that differs from
one state to another is not considered to be convincing enough. Calling this argument into
question then makes the variations recorded from one state to another more difficult to
explain.
The article from the McCartt team, which is extending its prior research, is not isolated (Foss
et al., 2009; Kolko, 2009; Nikolaev et al., 2010). The simultaneous publication of this research
indicates going further, if not a renewal, in the assessment of the impact of laws that ban or
restrict mobile phone use while driving. This is of course linked to the rapid increase in
subscriptions and to the diversification of the possible uses of cell mobile phones, over these
Collective Expert Report
- 104 -
13/12/2011
last few years, but it is also to be associated with a growing interest in governments for this
question. The interrogation developed by Nikolaiev and by Kolko differs however from that
of previous research. It does not entail assessing if the law is followed by a change in driver
behavior and if the latter persists over time, but rather if it reduces the risk of an automobile
accident, i.e. if it makes the roads safer (Nikolaiev et al., 2010).
The objective is different and as such the data used is also different, even if, here again, the
Nikolaiev study addresses the state of New York. Kolko and his colleagues are interested in
six American states that adopted a "hands-free" law, keeping in mind that in California and
in the state of Washington, the latter are effective only since July 2008. The conclusions of this
research therefore are not based on data drawn from observing drivers or from attitudes
declared at successive periods; it is based on accidentology before and after the adoption of
the legislation and recourse to tools for statistical analysis. Very roughly, the observation of
Nikolaiev et al. is that of a decline in the rate of fatal accidents as well as that for accidents
with injuries. Kolko associates the ownership of a cell mobile phone with more accidents but
only in the case of inclement weather and wet roads. The "hands-free" law would reduce
traffic accidents when driving conditions are degraded, which suggests increasing
surveillance during these rather particular periods (Kolko, 2009). But, one of the major limits
in these studies, recognized by their authors, is that legislation banning hand-held mobile
phones is not the only factor that could have affected the rate of automobile accidents during
the periods that were examined (Kolko, 2009; Nikolaiev et al., 2010). Kolko does however try
to include the various factors in the study's model.
This research was carried out in the Anglo-Saxon world and is not neutral, as is particularly
shown in the research published in 2009 by Foss and his colleagues. This research, carried
out in North Carolina, addresses a law that, since 2006, has banned all mobile phone use for
young drivers under the age of 18! In order to grasp the effects of the legislation studied, the
team observes mobile phone use by young drivers from North Carolina, before and five
months after the adopting of the legislation. The observation was carried out in the afternoon
when the teenagers were leaving school. This population is also compared to that of the
young drivers from South Carolina, where this type of legislation does not exist. In addition,
the team surveyed, by mobile phone, parents and adolescents before and after the adopting
of the text. It entailed assessing the reception of the repressive and educative measures. The
results of the survey established that mobile phone use changed little between the studies
prior to and after the new legislation. About 9% of the teenagers observed were holding a
phone in their hand. Less than 1% were judged as using a hands-free mobile phone. Before
the law came into effect, half declared that the rarely or never spoke on the mobile phone
while driving. This percentage increases to 69% after the law went into effect, but for reasons
that are not linked to the law. In sum, the study concluded, five months after it was adopted,
that the restriction does not have any effect on mobile phone use by young drivers. This
methodological matching, which is rather thorough but also complex, does not in any way
recall the context of a survey that would be found in Europe and in France. The population
observed, for example, does not exist in France. This suggests to what degree it would be an
issue transferring research results from one space to another and from one period to another.
It therefore becomes hazardous to consider, using data collected in this way, public actions
that can be effective and efficient in France and more widely in Europe.
In order to summarize and include the conclusion of the McCartt article (2010), observed
several years after the adopting of the hands-free laws studied, hand-held mobile phone use
remains lower than it would be without the law, but the extent of this reduction in usage
varies in the cases observed. All of this research suggests even so that legislation, in order to
Collective Expert Report
- 105 -
13/12/2011
be effective, must be supported with the control and sanctions and by information
campaigns on the risk incurred in the event the law is violated (Brace et al., 2009; MacCartt et
al., 2010). In order to fully measure the effectiveness of public efforts, simply assessing the
impact of the law is not enough. The evaluation carried out must address all of the actions
implemented at a given moment and which accompany the legislation.
Measures that are disconnected from an analysis of public policies
The measures presented in the previous section and more particularly recourse to law,
aiming to ban, restrict and punish mobile phone use while driving, respond to a definition of
the problem of road safety and its solutions that some analysts feel are too restrictive. The
various measures or strategies for action adopted – repression, education and information –
refer to a "reference base" for road safety public policy which is substantially centered on
calling deviant driver behavior into question. The road safety approach is as such reduced to
supervising and controlling driving behavior (Gilbert, 2009). This framework, which has
widely imposed itself and is taken for granted, is characterized by the central place that it
gives to the driver, to the individual driving the vehicle in the understanding of the problem
of road safety. Accidents are the consequences of a driver's not complying with the rules, the
driver who pilots and is responsible for his vehicle, or possible a lack of rules. Road insafety
as such primarily returns the blame to issues that concern individuals.
This definition of the problem has its solutions. Most of the policies imagined logically strive
to supervise individual behaviors by setting down rules and applying measures so that they
are complied with (Gilbert, 2009) and tend to focus on everything that can alter the driver's
abilities: alcohol abuse, speed and, today, mobile phone use while driving. Governments
then tend to build mono-causal responses and address abstract and isolated individuals that
they reduce to their legal and also moral obligations, which is shown well in the research of
Gusfield (2009). "Good driving conduct" is most often reduced to "good personal conduct".
Yet, the act of driving is an act that is situated and subjected to a multitude of constraints
(family, professional, environmental, etc.) for which it is also suitable to act for increased
effectiveness of public action. Not only is the analysis of the problem only partial, but it leads
to developing solutions which is turn are also only partial. Some responses are retained to
the detriment of others and are shown moreover to be limited in their effects, as suggested
by the analysis of prevention "strategies" that can be used by those in charge of road safety
policies (Brenac, 2004). Repressive strategies have effects that are not sustainable. Education
and training have mitigated effects. As for communication, this must be accompanied by
repression in order to have a minimum degree of effectiveness.
Of course, this reading of taking the road safety problem into account has limits. First of all,
the observation of the "domination" without sharing in the behavioral paradigm is an
exaggeration. There are definitional struggles and therefore the situation is not frozen:
"accidents have been and still are the object of competition between several definitions"
(Gilbert, 2009). As such, we can mention research that underlines the vigilance or distraction.
For Tingvall et al. (2009), for example, our safety systems need to be designed starting with
the hypothesis that the driver is subject to distraction and that vehicles incorporate everincreasing sources of technological distraction. The sponsors of these alternative definitions
are not necessarily lacking in resources and means to get their voice heard. The action of
stakeholders such as automobile manufacturers, insurers, engineers and sometimes even
researchers must not be neglected, a priori. The latter have provided and are still providing
out-and-out solutions in ascertaining the problem inspired by the behavioral paradigm
(Hamelin and Spenlehauer, 2008). Then, the link that is often built between dominant
Collective Expert Report
- 106 -
13/12/2011
representation of the problem and the policies that are implemented is not demonstrated.
Governments know how to make use of the various instruments or various strategies that
are available to them and all of these do not pertain to the strict application of the law and
control for this application. The history of road safety policy in France provides an
illustration of this. Public action here has addressed improving the "black spots" and
increasing the sanction as well as a calling for the participation of associations.
In fact, these critiques on the domination of the behavioral paradigm are based on the idea,
which is largely shared in the community of researchers on road safety, that an accident is
not so much the symptom of incorrect behavior as it is that of an error, of human failure and
that answers must be organized around error management, with tolerance for a margin of
error in the man-vehicle-infrastructure system (Reigner, 2004). This hypothesis falls in line
with wider thought on the risk and safety policies aiming to have the errors and the failures
recognized as being part of the ordinary operation of the complex sociotechnical systems that
form our environment (Gilbert et al., 2007). In terms of road safety, this diagnostic has the
merit of restoring the act of driving in a set of interactions between, of course, the driver, the
infrastructures and the vehicle, which today incorporates an ever-increasing range of onboard technological equipment. This representation relativizes the importance of the role of
the driver and calls for a sharing of responsibilities with vehicle designers, equipment
designers, governments, employers, etc. This falls in line with the idea of the "integrated
chain of safety" (Tingvall et al., 2009). But, in an approach that is more sociological than
technological, such a notion implies taking into account the multitude of stakeholders that
need to be involved in building and remaining attentive to the procedures to be
implemented in order to achieve this.
Beyond the image, the notion of a chain requires the joint and coordinated intervention of
the various stakeholders. Several research treating telephoning while driving indeed
underline indeed the interest of many stakeholders for the issue of regulating mobile phone
use while driving: consumers, politicians, experts and interest groups (Hahn et al., 2000).
But, either these texts simply just mention these, or they are limited to launching a call "for a
joint effort" from all (Tingvall et al., 2009), which would make it possible to reach a
standardization for on-board telephony devices. There is no reflection on the "feasibility" or
on the institutional systems to be built in order to structure a joint effort. Hammer (in
Tingvall et al., 2009) is an exception by mentioning Australian cooperation built on a
partnership policy which even so is conventional: The Cooperative Research Centre for Advance
Automative Technology brings together resources from the government, the University and
manufacturers (Tingvall et al., 2009). The most widespread logistics is based rather on the
idea that each of the stakeholders must, in the field which is more particularly theirs, take
their responsibilities concerning the use of a cell phone.
The scientific results obtained and the solutions proposed are indeed hardly discussed and,
in the case studied here, by the plurality of stakeholders interested in the use of telephony
devices while driving. There is little or no structured thought from these stakeholders (public
authorities, manufacturers, operators, experts, insurers, employers, employees, etc.) of which
the resources, interests, knowledge and capacities for mobilization are differentiated. As
such, there is little or no convergence. The opinion of a lobbyist indeed has a strong chance of
remaining unchanged, including when faced with solidly-argued expertise. It must also not
be ignored that the stakes with safety are only, for some stakeholders, one priority among
others and are therefore subject to arbitrage that is more or less likely to be supervised by
governments; this is the case with automobile manufacturers. They are, on the contrary, for
other much more central and even their sole reason for reacting, this is the case with
Collective Expert Report
- 107 -
13/12/2011
associations for victims, for example. Better yet, today, the value of a collective decision and
its legitimacy in obliging citizens is the result of its rationality as well as this decision being
taken after extensive and free discussion. An additional approach in mobilizing scientific
knowledge would therefore be based on the consultation and debating of the collective
stakeholders involved.
Without a doubt, we must look towards developing pluralistic and participative assessments
that would associate the major stakeholders in the policy evaluated and the population. This
type of approach aims to incorporate into the various phases of the assessment process the
highest number of parties interested in a public action program. This entails obtaining data
that is more reliable as well as more information than what would be collected external
experts in implementing the evaluated program, by associating in particular the operators
involved in the implementation, and to allow the latter to learn thanks to the information
received and exchanged and to the critical examination of the stakes at hand. Collecting the
opinion of the associated groups and their interactions can as such make it possible to better
situate the political debate (Blais, 2010) and therefore assist in a better consideration of the
possible consensuses in order to amend the legislation effectively. In sum, in order to
develop effective public action in this field, it is necessary to initiate a process that is of an
assessment nature as well as debatable, making possible not necessarily a co-decision but
more modestly a co-interpretation of the results of the assessment research. This indeed
entails favoring or facilitating the application, in the public action, of knowledge stemming
from research and expertise. A co-interpretation of the results of this research would in
particular allow for experts to better take the decisional context into account, wherein they
develop their recommendations (Abelson et al., 2003), and for governments to make use of it
in a way that is genuinely directed towards problem solving.
In conclusion, recourse to legislation is a privileged instrument by the government for action
in fighting against mobile phone use while driving. It first strives to change the behavior of
drivers, either by imposing the conditions for usage – "hands-free" laws have been adopted
by almost all of the authorities that have set down legislation on the subject – or by setting
restrictions according to his status. Recourse to law cannot therefore be considered using a
binary matrix: banning or authorizing the use of a cell mobile phone device during the act of
driving. The government can attack mobile phone use while driving by using its legal
powers of course, but also the information at its disposal, its financial resources and its
organizational capacities. Yet, it does not have a toolbox that it can draw from indifferently.
Then, none of these instruments has for sole objective to change driver behavior. They can
also be used to encourage other stakeholders to better take into account the stakes of road
safety that are inherent to mobile phone use while driving. Finally, the various measures
cannot be considered independently in relation to one another. It is more suitable to give
thought to an action program in terms of the "integrated safety chain" (Tingvall et al., 2009)
which would allow more particularly for the development of actions on vehicles in a close
relationship with interventions aimed at supervising the behavior of the users of telephony
tools during their travels on the road.
The measures that are effectively adopted are criticized in existing literature. They are
criticized not only because it is suitable to better target the recipients of the action of
governments and to further mix the instruments available to effectively fight against
behaviors at risk. The measures are also criticized because their impact on behaviors as on
accidentality has hardly been assessed. Tools should be available making it possible to
accumulate scientific proof as to the effectiveness of the measures taken and those being
considered. But recourse to the results of scientific research alone cannot enlighten decision
Collective Expert Report
- 108 -
13/12/2011
making. This review also suggests the pertinence of a pluralistic and participative
assessment which would bring together the various stakeholders. Each of the groups of
stakeholders affected by the measures that are decided can have diverging points of view,
according to their values, identity, needs and interests, which gives rise to uncertainties as to
the potential effects of the decisions that are effectively made.
BIBLIOGRAPHY
ABELSON J, FOREST PJ, EYLES J, SMITH P, MARTIN E, GAUVIN FP. Deliberations about
deliberative methods: issues in the design and evaluation of public participation processes. Social
Science and Medicine 2003, 57: 239-251
BLAIS E. L’évaluation d’impact sur la santé du code de la sécurité routière au Québec: le cas du
téléphone cellulaire au volant. Actes du séminaire « Évaluation d’impact sur la santé: méthodes
diverses d’analyse », Centre d’analyse stratégique, Paris, January 28, 2010, 43-53
BRACE CL, YOUNG KL, REGAN MA. The use of mobile phones while driving. Swedish road
administration, 2009
BRENAC T. Insécurité routière: un point de vue critique sur les stratégies de prévention. Espaces et
sociétés 2004, 118: 113-132
DINKELACKER TH. Driving distracted while in your employ: liability involving cell phones.
Psychologist-Manager Journal 2005, 8: 165-175
FOSS RD, GOODWIN AH, McCARTT AT, HELLINGA LA. Short-term effects of teenage driver cell
phone restriction. Accident Analysis and Prevention 2009, 41: 419-424
GILBERT C. Le risque routier: problème de « sécurité routière » ou problème de santé publique ? In:
Comment se construisent les problèmes de santé publique ? GILBERT C, HENRY E (eds). Paris, La
Découverte, 2009
GILBERT C, AMALBERTI R, LAROCHE H, PARIES J. Errors and Failures: Towards a New Safety
Paradigm. Journal of Risk Research 2007, 10: 959-975
GUSFIELD J. La culture des problèmes publics. L’alcool au volant: la production d’un ordre
symbolique. Economica, 2009
HAHN R, DUDLEY P. The disconnect between law and policy analysis: a case study of drivers and
cell phones. Working Paper, AEI Brookings Joint Center for Regulatory Studies, May 2002, 56p
HAHN RW, TETLOCK PC, BURNETT JK. Should you be allowed to use your cellular phone while
driving ? Regulation 2000, 23: 46-55
HAMELIN F, SPENLEHAUER V. L’action publique de sécurité routière en France. Réseaux 2008, 1: 4986
INSPQ (INSTITUT NATIONAL DE SANTÉ PUBLIQUE DU QUÉBEC). Effet de l’utilisation du
cellulaire au volant sur la conduite automobile, le risque de collision et pertinence d’une législation.
2006
INSPQ (INSTITUT NATIONAL DE SANTÉ PUBLIQUE DU QUÉBEC). Avis de santé publique sur les
effets du cellulaire au volant et recommandations. 2007
JANITZEK T, BRENCK A, JAMSON S, CARSTEN O, EKSLER V. Study on the regulatory situation in
the member states regarding brought-in (i.e. nomadic) devices and their use in vehicles. SMART
2009/0065, 2010
KALIN MC. The 411 on cellular phone use: an analysis of the legislative attempts to regulate cellular
phone use by drivers. Suffolk University Law Review 2005, 39: 233-262
KOLKO JD. The effects of mobile phones and hands-free laws on traffic fatalities. The BE Journal of
Economic Analysis and Policy 2009, 9: art. 10
Collective Expert Report
- 109 -
13/12/2011
LAMBLE D, RAJALIN S, SUMMALA H. Mobile phone use while driving: public opinions on
restrictions. Transportation 2002, 29: 223-236
MCCARTT AT, GEARY LL. Longer term effects of New York State’s law on drivers’ handheld cell
phone use. Inj Prev 2004, 10: 11-15
MCCARTT AT, HELLINGA LA. Longer term effects of Washington, DC, law on drivers’ hand-held
cell phone use. Traffic Injury Prevention 2007, 8: 199-204
MCCARTT AT, BRAVER ER, GEARY LL, Drivers’use of handheld cell phones before and after New
York State’s cell phone law. Preventine Medicine 2003, 36: 629-635
MCCARTT AT, HELLINGA LA, BRATIMAN KA. Cell Phones and driving: review of research. Traffic
Inj Prev 2006, 7: 89-106
MCCARTT AT, HELLINGA LA, STROUSE LM, FARMER CM. Long-term effects of handheld cell
phone laws on driver handheld cell phone use. Traffic Injury Prevention 2010, 11: 133-141
MICHAEL JB. Automobile accidents associated with cell phone use: can cell phone service providers
and manufacturers be held liable under a theory of negligence? Richmond Journal of Law & Technology
2005, XI: 1-25
NIKOLAEV AG, ROBBINS MJ, JACOBSON SH. Evaluating the impact of legislation prohibiting
hand-held cell phone use while driving. Transportation Research Part A 2010, 44: 182-193
O’MEARA M, BEDFORD D, FINNEGAN P, HOWELL F, MURRAY C. The impact of Legislation in
Ireland on Handheld Mobile Phone Use by Drivers. Irish Medical Journal 2008, 101: 221-222
PACHIAUDI G. Les risques de l’utilisation du téléphone mobile en conduisant. Les collections de
l’INRETS, Synthèse n°39, November 2001
PACHIAUDI G, MORGILLO F, DELEURENCE P, GUILHON V. Utilisation du téléphone main-libres:
impact de la communication sur la conduite automobile. INRETS report n° 212, November 1996
RAJALIN S, SUMMALA H, POYSTI L, ANTEROINEN P, PORTER BE. In-car cell phone use and
hazards following hands free legislation. Traffic Inj Prev 2005, 6: 225-229
REDELMEIER DA, TIBSHIRANI RJ. Association between cellular telephon calls and motor vehicle
collisions. The New England Journal of Medicine 1997, 336: 453-458
REGAN MA, LEE JD, YOUNG KL. Driver distraction. Theory, Effects and Mitigation. CRC Press, 2009
REIGNER H. La territorialisation de l’enjeu « sécurité routière »: vers un basculement de référentiel ?
Espaces et sociétés 2004, 3: 23-41
SUNDEEN M. Cell phones and highway safety 2006 state legislative update. National conference of
state legislatures, 2007. http://www.ncsl.org/print/transportation/2006cellphone.pdf
TEARLE P. Safe driving for business. Commun Dis Public Health 2004, 7: 158-160
TINGVALL C, ECKSTEIN L, HAMMER M. Government and Industry perspectives on Driver
Distraction. In: Driver distraction. Theory, Effects and Mitigation. REGAN MA, LEE JD, YOUNG KL
(eds). CRC Press, 2009, 603-621
TUNBRIDGE R. Mobile phones and driving-the UK perspective on government policy. International
Journal of Vehicle Design 2001, 26(1): 96-99
Collective Expert Report
- 110 -
13/12/2011
8
Socioeconomic impact of the ban on telephoning while
driving
There are very few economic analyses concerning road safety in France. For a long time, road
safety economy was reduced to a qualitative and very roughly quantitative assessment of the
costs at play in road safety (Le Net, 1992; Boiteux et al., 1994; Quinet, 2000; Boiteux and
Baumstark, 2001; Circulars from the Ministry of Infrastructure including that of 2005).
Except for some instances of research carried out for the most part within INRETS (for
example, Jaeger, 1997; Carnis, 2001; Dahchour, 2002; Lahatte et al., 2007), most of the research
in terms of road safety economy carried out in France up until recently have entailed
counting the number of deaths and injuries and the valorization of human life and injuries
(serious or light) in order to incorporate this dimension into transport infrastructure
profitability analyses. This entailed an approach in terms of econometric calculation applied
in particular to the economic profitability of infrastructure projects (Maurice and Crozet,
2007).
No research has been carried out to date in France on the socioeconomic impact of a ban on
mobile phone use while driving. However, the cost of road insafety is such that a
socioeconomic evaluation of all of the measures that are likely to reduce it is more than
justified. As such, the cost of road insafety is estimated for France, based on official values, to
be 23.7 billion euros for 2009, of which 10.7 for personal injury accidents (ONISR, 2010), and
the cost of damage is estimated for Europe to be 2% of the gross domestic product of the
European Union by Baum et al. (2010), which falls within the average of developed countries
(Connelly and Supangan, 2006). An evaluation of the economic impact of a ban on
telephoning while driving is also justified with regards to the potential consequences for
mobile telephony operators who generated 22.7 billion euros in sales in 2008, which is 1.1%
of France's GDP, or for households for which mobile mobile phones, all services taken as a
whole, entails on the average 1.4% of the budget (Idate Consulting and Research, 2009).
In fact, the rare research carried out on assessing the measures taken to counter mobile
phone use while driving was carried out in the Anglo-Saxon countries (United States,
Canada, Australia). The issue of evaluating the practice linked to hands-free kits is very
rarely addressed as such in this research which simply includes the results of the behavioral
studies (Redelmeier and Tibshirani, 1997; Strayer et al., 2006) which do not show that a
hands-free mobile phone is safer than a hand-held mobile phone. However, Hahn and
Prieger (2005), following Hahn and Dudley (2002), feel that the literature makes a connection
too easily between mobile phone use and accidents and that other factors must be decorrelated, such as age, sex, the power or size of the vehicle, etc. Based on a study of 7,000
people who had provided information of their mobile phone use and their accidents, they
found a relative risk of 1.4, much less than the relative risk of Redelmeier and Tibshirani
(1997) which was abundantly relayed in literature, but the risk measured is not exactly the
same. They even find a relative risk of 0.73 for hands-free mobile phone users. In the end,
they show that a ban on hands-free mobile phone does not lead to a statistically significant
reduction in the number of accidents.
Collective Expert Report
- 111 -
13/12/2011
However, even by not attributing the hands-free mobile phone with additional virtues in
relation to hand-held mobile phone, which is the most commonly accepted hypothesis,
Redelmeyer and Weinstein (1999) conclude that a selective restriction of the hand-hand
mobile phone and not the hands-free mobile phone would yields lower costs and benefits in
absolute numbers, but the same cost-effectiveness ratio.
All of this research refers to uses of the mobile phone which are rapidly changing, in terms of
volume as well as in terms of type of use. However, a certain amount of information can be
drawn from these studies and will make it possible to direct other research to be carried out
for France.
Socioeconomic evaluation as a decision-making tool
Socioeconomic evaluation for transportation projects was born out of the necessity to
develop tools making it possible to compare the different variants of an infrastructural
project with one another and more globally to assess its potential impact. Performing a
socioeconomic evaluation of road safety measures or more generally of a measure or
transportation policy supposes that all of the advantages and disadvantages linked to the
measure in question are taken into account and to assess these for the collective whole.
Cost-benefit analysis
The most commonly used method of evaluation, in France as well as abroad to evaluate the
socioeconomic impact of a transportation project, is the cost-benefit analysis. This consists in
carrying out an up-to-date assessment of the gains and losses linked to a measure, for
example the ban on telephoning while driving, for all of the stakeholders involved (users,
companies, the State or local authorities) and which takes into account all of the monetary
elements (financials) and elements that can be monetarized (time, safety, noise and
pollution). In order to respond in part to critics made concerning cost-benefit analysis, in
particular the producing of aggregate indicators, Van Malderen and Macharis (2010) suggest
developing analyses of the Mamca (Multi-Actor Multi-Criteria Analysis) type, in order to
enhance the cost-benefit analysis through a better identification of the stakes and
stakeholders and through a decomposition of the indicators and results according to the
stakes and stakeholders (systematic decomposition of the excess per stakeholder, i.e. of the
difference between the gains and the losses for each stakeholder, for example). They do not
however question the interest per se of a cost-benefit analysis as a decision-making tool.
As such, the cost-benefit analysis incorporates the following financial elements: the costs of
the measure or of the policy (for example, costs links to mobilizing the police forces for the
control or the cost of the information campaign); the financial gains or losses for the various
stakeholders (as such, a ban on the mobile phone would fully eliminate the costs and the
gains of calls for the users and the expenses of the health system, as well as the gains for
garage owners, certain employers and telephony operators, etc.).
The time (saved or lost) is monetarized by a time value, often calculated on the average
hourly wage, but which can vary according to several parameters (reason for travel, urban or
inter-urban, etc.). With regards to a ban on telephoning while driving, it is not so much the
impact in terms of travel time that is saved or lost that can be pertinent in the measure
(except when considering that calls not made while driving result in stopping the vehicle in
order to call which as such increase the total travel time) than the value of the mobile phone
calls made or received. However, the existence of lost time linked to the congestion caused
by accidents due to telephoning while driving can also be considered.
Collective Expert Report
- 112 -
13/12/2011
The gains in terms of road safety are apprehended through the number of human lives and
injuries (serious or light) that are spared, with these numbers valorized by a value for human
life (estimated value or official value, with the official value being the value that the
collective whole is ready to assume in order to save a human life or avoid an injury).
Two main indicators are used in order to judge the socioeconomic profitability of a project or
measure. The first is the net book value which is the discounted total (at the discount rate
defined by the State, according to its investment capabilities, which is currently 4% in
France) of all of the advantages and disadvantages of the project or measure over a given
period of time, generally 30 years for an infrastructure project or 10-15 years for an on-board
system of which the life time will not exceed this period of time. The second is the economic
rate of return, which is the value of the discount rate that cancels out the discounted benefit.
If the rate of return is higher than the discount rate retained by the public power, the project
or the measure will be considered to be of interest for the collectivity, from a socioeconomic
standpoint.
In the rare research addressing the assessment of the impact of telephoning while driving
(Redelmeyer and Weinstein, 1999; Hahn et al., 2000; Cohen and Graham, 2003; Sperber et al.,
2009), the discount rate taken into account is the same, which allows for the comparison, and
this is 3%. This rate of 3% is also used to assess other projects as in the case with a dozen
safety systems for smart vehicles (Baum et al., 2010). This rate is moreover very close to the
rate of 4% that has been adopted by France since 2005. This "rather low" rate gives somewhat
of a priority to the future or rather to the "good" taking into account of the expected effects in
the future of the measures taken at a given moment.
Socioeconomic evaluation of road insafety
The issue of the cost or of the value of accidents has given rise to much research work. The
social benefit of a measure for banning telephoning while driving lies in a decrease in the
number of deaths and injuries and in a socioeconomic valorization of the latter. This
valorization is carried out based on the use of values attributed to human life or to injuries.
These values can be official values, which we will address shortly, or values estimated via
various methods. These same methods can moreover be used to define the official values.
Several methods exist to assess the socioeconomic consequences of deaths and injuries on the
road.
A commonly-used method is the human-capital method, which aims to assess the losses for
society not only in direct costs, but also in terms of a loss in production or non-merchandise
losses, such as the quality of life. As such, the human costs (medical, ambulance and
rehabilitation costs; health costs over time, work-related losses, quality of life, costs for
replacing manpower, funeral costs, etc.), material damage to vehicles and the other costs
(claims management costs for insurance companies, delays, police, other material damage,
fire department, etc.) can be distinguished. Connelly and Supangan (2006) estimate that
human costs represent more than 56% of the costs of road insafety in Australia in 2003,
material damage to vehicles 27% and other costs 17%. This is the method that was used in
the evaluations listed in this chapter concerning the ban on telephoning while driving.
In the approaches in terms of human capital, production losses due to a death or serious
injuries are definitively lost for society, which can lead to overestimating these indirect costs.
The friction-cost method has been suggested as an alternative to the human-capital method
in order to better approach production losses linked to short-term absenteeism (Lopez
Bastida et al., 2004; Connelly and Supagan, 2006). This is referred to as friction costs since the
loss of a worker only causes transitory or frictional losses until another worker replaces the
Collective Expert Report
- 113 -
13/12/2011
worker who died or was injured. In the theory, if the labor market is perfectly elastic, the
replacement takes place immediately and production losses are close to zero (Connelly and
Supangan, 2006).
Another evaluation method is the indemnification cost evaluation method, i.e. what the
insurance companies pay to the victims. As such, the provisioned indemnification cost by the
FFSA (French federation of insurance companies) in 2006 was 3.9 billion euros. This amount
is far less than the 11.6 billion euros which correspond to the valorization of road insafety in
2006 carried out on the basis of official values (Chapelon, 2008).
This result indeed shows that the choice of the method and then the values retained for
human life and injuries is far from having a neutral effect on the result of the evaluations.
For some authors, the official values retained by States are too low and they recommend
using the willingness-to-pay method, a method which in fact most often results in higher
values for human life. Indeed, for Baum et al. (2010) individuals are ready to pay very high
amounts in order to reduce the probability of a premature death regardless of their level of
productivity. For Lahatte et al. (2007), this method has also been successful with young
drivers who are aware that accidents can cause effects that they would not like to undergo,
since 84% of them would accept to pay in order to avoid this, with the amount of the
willingness-to-pay then highly dependent on the individual's revenue. This willingness-topay indicates a preference to reduce the risk of becoming injured, or even killed in an
accident. For Baum et al. (2010), the data available seems to indicate that these values are
fundamentally higher than the cost of the damage and in particular they mention the figure
of 5.7 million euros per victim, calculated by Flemish researchers. In another case, Wijnen et
al. (2009) show that the official value calculated on the basis of the willingness-to-pay
method would be at least 1.6 million euros (value 2001) in the Netherlands, which is higher
than the values that are usually used by the States, including France where the official value
of human life is 1 million euros (value in 2000).
In order to measure the willingness-to-pay, there are primarily two main methods: the
revealed-preference method (the value is deduced from the behavior of individuals, through
their practices, the purchase of an airbag for example) and the declared-preference method
according to which the individuals are asked to state the value that they attach to a service or
a state of health. Declared preferences are generally used when there is no data to allow for
an approach in terms of revealed preferences (Connelly and Supangan, 2006). Svensonn
(2009) goes along with the critique on the declared-preference methods according to which
what is declared has many biases and shows, by targeting the "sure" responses, that the
range of estimations can be tightened with a value of human life estimated between 2.9 and
3.1 million euros in Sweden. De Blaeij et al. (2003) address the issue of the substantial
variation in literature of the official value of human life and confirm that revealed-preference
methods yield values that are lower than declared preferences.
Official value of human life and its use
The official value of human life reflects the priority that is attached at a given moment by the
collectivity, here the State, in valorizing the reduction in the number of fatal accidents in the
socioeconomic assessments carried out for the major infrastructure projects. As such, in
France, any measure that will make it possible to avoid a fatal road accident will have its
monetarized assessment increase by 1 million euros (value 2000), and by 150,000 euros for a
serious injury and 22,000 euros for a light injury. These official values were set down after
political arbitrage and are based on a number of studies in France and in Europe in order to
Collective Expert Report
- 114 -
13/12/2011
determine what could be this average cost for life (Boiteux and Baumstark, 2001). These
values are then discounted according to the household consumer spending index.
The definition of the official values is at the heart of the evaluation issues and of course
conditions the very results of the evaluations carried out. As such, Faivre d’Arcier and
Mignot (1998) carried out a sensitivity analysis of the result in terms of rate of return for a
transportation infrastructure project, according to a variation of the various parameters taken
into account in the calculation, with the latter performed according to the rules of the
circulars of the Ministry of Infrastructure at the time. They showed that a variation of plus or
minus 10% in the investment cost of the project or in the cost of using a car had a similar
impact, of a magnitude of plus or minus 6%, on the rate of socioeconomic profitability of the
project, obviously reflecting the very important role of these two parameters in the
economics of the project.
Inversely, a variation of plus or minus 10% of the official values taken for the social costs
relating to road safety or the environment had only a very limited impact on the rate of
return, 0.06% for the local pollution, 0.3% for noise and 0.6% for the value of human life,
while at the same time the impact of a 10% reduction in the time value would reduce the rate
of return by 2.6%.
Faivre d’Arcier and Mignot (1998) thus concluded in 1998 that the official values used at the
time for road safety and the environment were not, in any way, able to call into question a
project for creating a new road infrastructure and that it would have been necessary to
multiply these values by ten. We can state that the official value of human life in 2010 is 1
million euros (value in 2000), which is about twice the value used in the circular of 1995,
following the recommendations in the Boiteux report (Boiteux et al., 1994), i.e. 3.7 million
francs.
We therefore agree with Wijnen et al. (2009) when they conclude that taking lower official
values contributes in making the result of the cost-benefit analyses less interesting and
therefore in putting off road safety policies which are however necessary and which would
be able to be socioeconomically justified with higher official values.
From the number killed to the number of good health years
Recent research that has been developed primarily in health economics would make it
possible to renew the approach by specifying this notion of the average cost of human life
using research on life and health indicators (Connelly and Supangan, 2006; Wijnen et al.,
2009; Vaillant and Dervaux, 2010). The objective is no longer just to count the number of lives
saved but also to introduce elements pertaining to the quality of life, through for example the
number of years of life in good health or the number of years of life with a disability.
As such, QALYs (Quality-adjusted life years) make it possible to incorporate the duration of
life and the quality of life. This type of approach is useful in health to compare the effects of
different treatments or interventions by introducing this quality of life dimension after
"intervention" or without intervention. Obviously, the "value for a year of life in good health"
raises the same type of issue as "value of human life" put forth by transportation economists
and the tools available to economists and deciders are not so different when they are
mobilized within the framework of a cost-benefit type analysis. The approach via QALYs
moreover makes it possible to raise the question of better use of a budget in order to carry
out an action.
DALYs (Disability adjusted life years) also reverts to a counting of years of life but these years
are adjusted by the disability. This then entails evaluating the number of years of life saved
Collective Expert Report
- 115 -
13/12/2011
or provoked for one or more given levels of disability (measured as a running succession of
handicaps).
The interest afforded by these types of approaches to road safety can be seen immediately, in
a context where the number of deaths is effectively on a downward trend, but wherein the
increased awareness of the stakes for the injured is recent. An approach of the QALYs or
DALYs type, applied to road safety and more generally to the decisions concerning
infrastructures and transportation policies, would make it possible to not doubt
strengthening the view on the injured, including the seriously injured, who are a major stake
in terms of road safety.
These approaches are already in use and applied, in particular in the United States and in
Canada, in assessing a ban on telephoning while driving as we shall see further on.
A few examples of the use of economic evaluation for measures in favor of road safety
Economic analysis has been mobilized to economically evaluate Automated sanction control
(Cameron and Delaney, 2010) or to set the basis for it for France (Carnis, 2010). Note however
that this research, which compare the cost of deployment and the advantages in terms of
safety do not take into account the valorization of the time lost by the users. As such,
although the evaluation of the impact of the automated sanction control had been carried out
in France (ONISR, 2006), it only addresses however the impact in terms of accidentology and
does not provide an overall economic evaluation of the system.
Economic analysis is also used to evaluate on-board systems, whether in France with the
evaluation of the economic acceptability of systems developed within the Sari project
(Automated road surveillance for driver and operator information) (Deregnaucourt, 2008), or
in Germany with an evaluation and a comparison of various on-board driving assistance
systems, such as for example electronic stability control or speed alert (Baum et al., 2010).
Lindberg et al. (2010) also mobilize an economic approach in order to test various means
aimed at encouraging automobile owners to install an electronic device in their vehicle that
can encourage them to limit excessive speed. They show also that an indemnity intended to
compensate those who accept the device, for example a reduction in their insurance
premium, increases the propensity of drivers to accepter this system.
Economic question of the ban on telephoning while driving
The specific issue of telephoning while driving is by definition recent as it is linked to the
appearance of the latter and to the generalization of its use.
International literature on the economic question of the banning of telephoning while
driving is meager. These studies carried out at the end of the 1990's and at the beginning of
the 2000's (Redelmeyer and Weinstein, 1999; Hahn et al., 2000; Hahn and Dudley, 2002;
Cohen and Graham, 2003) show that there is no economic justification in banning
telephoning while driving in general (hand-held and hands-free). The most recent research
on the United States (Cohen and Graham, 2003) shows at best that there is a balance between
the gains (in terms of the economic valorization of the accidents avoided) and the losses (in
terms of the economic valorization of the mobile phone calls that were not made). However,
a study carried out in the province of Alberta in Canada suggests that under certain
conditions a banning of telephoning while driving could be interesting from a socioeconomic
standpoint (Sperber et al., 2009).
Collective Expert Report
- 116 -
13/12/2011
Economic evaluation of a law banning telephoning while driving in Anglo-Saxon
literature
Concerning the precise question of the socioeconomic evaluation of a ban on mobile phone
use while driving, two articles can basically be identified (Redelmeier and Weinstein, 1999;
Hahn et al., 2000) and one report (Lissy et al., 2000) which can be qualified as founding items.
They are the first research to treat the issue, and almost the sole ones, and were carried out
on the scale of the United States. They were updated or were made more precise (Hahn and
Dudley, 2002; Cohen and Graham, 2003; Hahn and Prieger, 2005), then comments were made
or they were included in the rare studies that followed, in particular by the latest available of
Sperber et al. (2009) carried out on Alberta.
Although many articles, of which some are very recent (Blais and Sergerie, 2007; White et al.,
2010) address the question of the link between cell phones and accidentology and treat the
comparison of hand-held mobile phones and hands-free mobile phones (Strayer et al., 2006),
very few address the economic question. A review of the literature carried out in 2007 (Brace
et al., 2007) on the use of cell mobile phones while driving devotes only one paragraph out of
48 pages to the economic question, and this paragraph simply states the results of the three
"founding" research efforts. In the assessment carried out by the TRB (Transportation Research
Board, 2010) of the publications presented to the TRB or published by the TRB on distractions
while driving, no study listed refers to the economic question.
In the same way, the research on evaluating road insafety or on the evaluation of road safety
measures gave little attention to the question of cell mobile phones while driving and even
less to the question of the socioeconomic evaluation of the hands-free mobile phone.
Reviewing the literature on the question of the cost-effectiveness assessment of road safety
measures in the United States, Vahidnia and Walsh (2002) observe that the methods used
vary substantially as well as the results, but they do not mention the question of the factors
and therefore of the mobile phone. In the same way, Connelly and Supangan (2006) who for
Australia analyzed the economic costs of road safety, providing details by type of injury and
by region, do not address the question of telephoning while driving. The attempt made by
Elvik et al. (2009) to do a cost-benefit analysis on research in road safety in Sweden over the
period 1971-2004, does not address the question of the cell phone, as Sweden has no
legislation concerning this.
Finally, other research does indeed identify a link between an economic context and road
accidents (Scuffham, 2003; Partheeban et al., 2008) but also does not address the question of
cell phones while driving.
Hypotheses retained by the studies on the socioeconomic evaluation of telephoning while
driving
With regards to the expected gains of a ban on mobile phone use while driving, the first
extensive study carried out in 1999 in the United States (Redelmeier and Weinstein,
1999) made it possible to say that the ban, by reducing the number of accidents, would allow
for gains of 1 million dollars a day for the health system and 4 million a day for the other
financial costs (insurance costs, taxes, travel delays, material damages, etc.). On a comparable
basis, Cohen and Graham (2003) estimate these potential gains to be 35.7 billion dollars per
year for the United States. Sperber et al. (2009) for Alberta, include in their calculation the
production losses linked to the death of agents with the ability to produce, estimated to be
90,000 dollars per injured person and 2.7 million dollars per death.
These studies suppose that, beyond the risks linked to the manipulation itself of the mobile
phone, the incremental risk of an accident is proportional to the time spent on the mobile
Collective Expert Report
- 117 -
13/12/2011
phone, due to the distraction effects. The vast majority of the studies (Redelmeier and
Weinstein, 1999; Cohen and Graham, 2003; Sperber et al., 2009) are thus based on Redelmeier
and Tibishirani (1997) which do not show that the hands-free mobile phone is safer than the
held-held mobile phone and are also based on Strayer et al. (2006) which confirms this. In
these studies, the relative risk of an accident on the mobile phone taken into consideration is
an average of 4.3. For a driving time per day and per driver estimated to be 60 minutes, the
time spent on the mobile phone was estimated to be 2 minutes a day for studies that were
done at the beginning of the 2000's (Redelmeyer and Weinstein, 1999; Hahn et al., 2000;
Cohen and Graham, 2003) and 3.6 minutes for the most recent study (Sperber et al., 2009).
There is without a doubt a portion of the explanation of the difference between the Sperber et
al. results and the other studies, in that they take an exposure time to the risk that is twice as
high, but which can be justified by an increasing use of the mobile phone, as this latter study
is more recent than the others. This point would need to be verified however in the case of a
study to be done for France.
With regards to the question of valorizing of mobile phone calls, literature has concentrated
more on the valorization of the time spent on the mobile phone. As such, the Redelmeier and
Weinstein study (1999) on the United States made reference to a time value for users of 0.47
dollars per minute, based on the value of the demand for this type of services (estimated
based on a change in demand and on the average prices in the market over the eight years
prior to the date of the study and reflecting the existence of demand even for the higher
prices that were observed as the beginning of the reference period). These values were
simply updated in the following studies carried out in the United States. The total value of
the mobile phone calls received or made while driving per year in the United States has as
such been estimated to be 12 billion dollars in 1999, 25 billion dollars in 2000 and 43 billion
dollars in 2003. The most recent study on Alberta (Sperber et al., 2009) differs, in that it
favors an approach in terms of elasticity of demand to price, with the latter being calculated
using an estimation of the revenue in the cell phone industry.
Inversely, the financial cost of the calls for users was estimated to 0.38 dollars a minute for
studies on the United States and at 0.12 dollars a minute (the lowest value of the two
estimations) for the study on Alberta also reflecting a relative drop in the unit cost of a
minute of communication. A banning of cell mobile phones would therefore result in these
cases in a loss for the industry.
In sum, the surplus for users in the United States, i.e. the difference between the value of the
call and the cost of the call for the user is estimated to be 0.09 dollars per minute by
Redelmeier and Weinstein (1999) and 340 dollars per person per year on the average by
Cohen and Graham (2003). The social benefit of a measure to ban telephoning while driving
residing in a decrease in the number of deaths and injuries is as such estimated at 43 billion
dollars on the average for the United States by Cohen and Graham (2003).
Finally, there are two important method points. The first, which we have already mentioned,
is that the various studies use the same discount rate of 3%, a value which indeed takes the
long-term effectiveness of a measure into account. The second relates to the estimation of the
rate of application of the law. The studies in the United States took a hypothesis of a rate of
application of the law of 65%. Sperber et al. (2009) introduce a probabilistic approach making
it possible to simulate the level of non-compliance with the law or rather the rate of
application of the law. The "rational" user will comply with the law if his time value is lower
than the amount of the fine that he risks having to pay in the event of a violation. Inversely, a
high time value associated with a low perception of the risk results in non-compliance with
the law.
Collective Expert Report
- 118 -
13/12/2011
Socioeconomic impacts of a ban on telephoning while driving
In the end, the overall assessment of banning cell mobile phones while driving is estimated
for the United States at a cost per QALY (quality-adjusted life year or year of life in good
health) of 300,000 dollars by Redelmeier and Weinstein (1999), at an annual loss of 23 billion
dollars by Hahn et al. (2000) (25 billion dollars in cost and 2 billion dollars in benefit) and at a
negative net benefit of 220 million dollars by Cohen and Graham (2003). This latter amount is
rather low, revealing a balance between socioeconomic advantages and disadvantages of a
ban on telephoning while driving. For Sperber et al. (2009), the estimation is that there is an
80% chance that a ban results in a gain and a 94% chance that a ban costs less than
50,000 dollars per QALY. The assessments therefore vary somewhat, according to these
different studies. As such, for the studies concerning the United States, a banning of cell
mobile phones is clearly not economically efficient for the authors of the first two studies
(Redelmeier and Weinstein, 1999; Hahn et al., 2000). For Hahn and Dudley (2002), the two
studies have similar results, but show differences. As such, Redelmeier and Weinstein (1999)
feel that mobile mobile phones are the cause of twice as many accidents than Hahn et al.
(2000). The data on demand seems to be finer in the second study which leads to higher
losses for consumers.
The assessment is more balanced for the Cohen and Graham study (2003). The authors feel
however that restrictions of the use of the cell phone while driving have a lesser costeffectiveness ratio for society than the other measures in terms of safety (example of lateral
airbags) or in other words there are actions that could be more effective in terms of reducing
accidents and at a lesser cost than banning the cell phone. Hahn and Dudley (2002) also
move in this direction, using the Lissy et al. study (2000), which, based on the first two
studies by taking the costs in Hahn et al. (2000) and the advantages in Redelmeier and
Weinstein (1999), compares the cost/effectiveness ratio of a ban on telephoning while
driving with eight other road safety measures. Out of the eight other measures, two would
make it possible to reduce costs (safety belt and daytime running lights) and four are less
costly than banning the mobile phone (front airbags, lateral supports, front airbags for
passengers, limiting the speed to 55 miles per hour). Only one measure is more expensive.
For Hahn and Dudley (2002), a ban on telephoning while driving would therefore be a costly
way of saving lives and far from being a good investment, compared to safety belts or
airbags. Even if their economic evaluation does not justify the ban on telephoning while
driving, Cohen and Graham (2003) do conclude however that drivers should avoid
unnecessary calls, have short conversations, and suspend the exchange in the event of
dangerous circumstances (but do not develop these any further) and that a ban for young
drivers (who have the most accidents) could be economically beneficial for society.
For the latest study to date (Sperber et al., 2009), a banning of cell mobile phones while
driving is potentially interesting in a society perspective. Sperber et al. show however that
the results are sensitive to parameters for which there is very little information, concerning
the value of calls, for example, or for which the information is contradictory, concerning the
risk for example. These authors also mention the question of a targeted ban for young
drivers who have the highest risk of accidents and consider that there is no "economic"
reason for banning the use of the mobile phone use while driving if the drivers "assume" i.e.
pay, for the damage caused.
The only study to cover the question of the hands-free mobile phone rather thoroughly is
that of Hahn and Dudley (2002). They show that the use of a hands-free mobile phone
contributes in fact to an increase in the direct and indirect costs of communications which
should reduce the demand for these communications. This extra cost is especially due to the
purchase cost of the hands-free kit. If we extrapolate on this result, we can hypothesize that
Collective Expert Report
- 119 -
13/12/2011
on-board systems, which have a higher cost than off-the-shelf hands-free kits, further
reinforce this logic. In the end, Hahn and Dudley (2002) conclude their review of the
literature in very clear way: “The economics and science on this issue are fairly clear: a total ban
does not seem to be justified on economic grounds and the effectiveness of hands-free devices in
reducing motor vehicle accidents is unclear “ (Hahn and Dudley, 2002, p49).
In conclusion, the reference research carried out on the scale of the United States show that
there is no socioeconomic justification in banning telephoning while driving in general
(hand-held and hands-free). Only the Sperber et al. study (2009) on the Province of Alberta
makes this conclusion.
In all of this research, the uncertainties and the biases are many and the results must
therefore be taken with precaution. But, all state that the final result in fact depends on a
single parameter which is the valorization of mobile phone calls, with the risk factor having
the least influence. The authors also converge to say that there are many other measures that
are better in terms of cost/effectiveness ratio, which should then be favored, such as lateral
airbags for example. Many techniques for limiting mobile phone use while driving can also
be imagined (better identify the activities that are more or less at risk and adapt mobile
phone use according to the activities; limiting the duration of mobile phone conversations;
allow only on-board systems that allow communications to be stopped in critical driving
situations, etc.).
The socioeconomic studies treated hand-held mobile phones, not hands-free kits, this latter
use, when it is mentioned, refers to the research on prevalence. A particular study in France
on the value of calls made from a hands-free kit would constitute an international reference.
The underlying hypothesis is that the value of the calls made from a more costly "tool"
would then too be higher, in which case, based solely on the economic criterion, the ban
would be even further less economically effective. As such, an increase in the cost of mobile
phone calls, if it is not marginal, should result in a decline in mobile phone usage. But the
changes in rates concerning cell mobile phones in the last few years are on the contrary going
down. Special rates for communications made or received from a vehicle in motion should
result in less mobile phone use while driving, and even usage that is limited to "strictly
necessary" calls.
Finally, the conclusion of several authors is that the question of the law is not only an
economic question. Indeed, the economic cost/effectiveness ratio for measures limiting
mobile phone use while driving depend above all on the value of the communications or on
official values for human life and the injured according to the methods used. As such a
measure that today is not deemed to be economically desirable can become so tomorrow,
with everything else remaining the same, if the retained values are higher. For example, if
the official value for human life approaches the value of 5.7 million euros per victim,
mentioned by Baum et al. (2010), this would lead to a multiplication by almost 6 of the value
used today for human life in France.
This would end up putting the question of political responsibility back in the center, as the
official values reflect only the priorities that the authorities give to the question.
BIBLIOGRAPHY
BAUM H, GEIBLER T, WESTERKAMP U. Rentabilité des véhicules intelligents. Méthodologie et
résultats à partir de l’étude eIMPACT. Les Cahiers Scientifiques du Transport, n° spécial Économie de la
sécurité routière: définition, connaissance et enjeux 2010, 57: 85-116
Collective Expert Report
- 120 -
13/12/2011
BLAEIJ (de) A, FLORAX RJGM, RIETVELD P, VERHOEF E. The value of statistical life in road safety:
a meta analysis. Accident Analysis and Prevention 2003, 35: 973-986
BLAIS E, SERGERIE D. Avis de santé publique sur les effets du cellulaire au volant et
recommandations. Institut national de santé publique du Québec, 2007, 97p
BOITEUX M, BAUMSTARK L. Transports: choix des investissements et coût des nuisances.
Commissariat Général du Plan, La Documentation Française, Paris, 2001, 323p
BOITEUX M, MATHIEU M, HALAUNBRENNER G. Transport: pour un meilleur choix des
investissements. Commissariat Général du Plan, La Documentation Française, Paris, 1994, 132p
BRACE CL, YOUNG KL, REGAN M. Analysis of the literature, The use of mobile phones while
driving. Monash University, Vägverket, 2007, n°2007-35, ISSN n° 1401-9612, 48p
CAMERON MH, DELANEY AK. Contrôles de vitesse: effets, mécanismes, densité et analyse
économique pour chaque mode d’intervention. Les Cahiers Scientifiques du Transport, n° spécial
Économie de la sécurité routière: définition, connaissance et enjeux 2010, 57: 63-83
CARNIS L. Entre intervention publique et initiative privée: une analyse économique en sécurité
routière, une application aux législations sur la vitesse. Thèse de doctorat, Université de Reims
Champagne-Ardenne, Faculté des sciences économiques et de gestion, 2001, 2 volumes, 726p
CARNIS L. Analyse économique des choix de vitesse: entre théorie et pratique. In: Pour une économie
de la sécurité routière. CARNIS L, MIGNOT D (eds). Economica, 2010
CHAPELON J. L’impact économique de la sécurité routière. Sève 2008, 4: 65-70
COHEN JT, GRAHAM JD. A revised economic analysis of restrictions on the use of cell phones while
driving. Risk Analysis 2003, 23: 5-17
CONNELLY LB, SUPANGAN R. The economic costs of road traffic crashes: Australia, states and
territories. Accident Analysis and Prevention 2006, 38: 1087-1093
DAHCHOUR M. Tarification de l’assurance automobile, utilisation du permis à points et incitations à
la sécurité routière: une analyse empirique. Thèse de doctorat, Faculté des sciences économiques,
Université Paris X Nanterre, 2002
DEREGNAUCOURT J. Méthodologie des études économiques réalisées dans SARI. In: Actes du
séminaire économie de la sécurité routière 2008. MIGNOT D (ed). INRETS report for the Predit, Paris,
2008, 123-126
ELVIK R, KOLBENSTVEDT M, ELVEBAKK B, HERVIK A, BRAEIN L. Costs and benefits to Sweden
of Swedish road safety research. Accident Analysis and Prevention 2009, 41: 387-392
FAIVRE D’ARCIER B, MIGNOT D. Using economic calculation as a simulation tools to assess
transport investments, Communication à la 8e Conférence Mondiale sur la Recherche en Transport,
Anvers, July 17-21 1998, 11p
HAHN RW, DUDLEY PM. The disconnect between law and policy analysis: a case study of drivers
and cell phones. AEI Brookings - Joint Center for Regulatory Studies, Working Paper, 2002, 56p
HAHN RW, PRIEGER JE. The impact of driver cell phone use on accidents. AEI Brookings, Joint
Center for Regulatory Studies, Working Paper, 2005, 51p
HAHN RW, TETLOCK PC, BURNETT JK. Should you be allowed to use your cellular phone while
driving ? Regulation 2000, 23: 46-55
IDATE CONSULTING AND RESEARCH. Observatoire économique de la téléphonie mobile: Faits et
chiffres 2008. Report for AFOM, Idate 2009, 41p
JAEGER L. L’évaluation du risque dans le système des transports routiers par le développement du
modèle TAG. Thèse de doctorat de Sciences économiques, Université Louis Pasteur, Faculté des
sciences économiques de Strasbourg, 1997, 347p
LAHATTE A, LASSARRE S, ROZAN A. Evaluation économique des conséquences d’un accident de la
route non mortel. Revue d’économie politique 2007/2, 117: 225-442
Collective Expert Report
- 121 -
13/12/2011
LE NET M. Le prix de la vie humaine: application à l’évaluation du coût économique de l’insécurité
routière. Commissariat Général du Plan, Paris, 1992
LINDBERG G, HULTKRANTZ L, NILSSON JE, THOMAS F. Payer selon sa vitesse. Deux expériences
de terrain destinées à limiter le risque de sélection adverse et le risque moral dans le secteur de
l’assurance automobile. Les Cahiers Scientifiques du Transport 2010, 57: 117-139
LISSY KS, COHEN JT, PARK MY, GRAHAM JD. Cellular phone use while driving: risks and benefits.
Harvard Center for Risk Analysis, Harvard School of Public Health, Boston, Massachusetts, 2000,
Phase 1 Report
LOPEZ BASTIDA J, SERRANO AGUILAR P, DUQUE GONZALES B. The economic costs of traffic
accidents in Spain. The Journal of Trauma 2004, 56: 883-889
MAURICE J, CROZET Y. Le calcul économique dans le processus de choix collectif des
investissements de transport. Collection « Méthodes et approches », Predit-Economica, Paris, 2007,
350p
MINISTÈRE DE L’ÉQUIPEMENT. Instruction cadre relative aux méthodes d’évaluation économique
des grands projets d’infrastructures de transport. Paris, 2005, 40p
ONISR. Impact du contrôle sanction automatisé sur la sécurité routière (2003-2005). Paris, 2006, 87p
ONISR. La sécurité routière en France, Bilan de l’année 2009. La Documentation Française, Paris, 2010,
315p
PARTHEEBAN P, ARUNBABU E, HEMAMALINI RR. Road accident cost prediction model using
systems dynamics approach. Transport 2008, 23: 59-66
QUINET E. Economic evaluation of road traffic safety measures. CEMT Round Table 117, Paris, 2000,
167p
REDELMEIER DA, TIBSHIRANI RJ. Association between cellular telephon calls and motor vehicle
collisions. The New England Journal of Medicine 1997, 336: 453-458
REDELMEIER DA, WEINSTEIN MC. Cost-effectiveness of regulations against using a cellular mobile
phone while driving. Medical Decision Making 1999, 19: 1-8
SCUFFHAM P.A. Economic factors and traffic crashes in New Zealand. Applied Economics 2003, 35:
179-188
SPERBER D, SHIELL A, FYIE K. The cost-effectiveness of a law banning the use of cellular phones by
drivers. Health Economics 2009, www.interscience.wiley.com.
STRAYER DL, DREWS FA, CROUCH DJ. A comparison of the cell phone driver and the drunk driver.
Human Factors 2006, 48: 381-391
SVENSONN M. The value of statistical life in Sweden: Estimates from two studies using the
« Certainty Approach » calibration. Accident Analysis and Prevention 2009, 41: 430-437
TRANSPORTATION RESEARCH BOARD. Publications on distracted driving. 2010, 38p
VAN MALDEREN F, MACHARIS C. Méthodes d’évaluation socioéconomique: regarder la forêt
plutôt que les arbres à partir d’un arbre de décision. In: Pour une économie de la sécurité routière.
CARNIS L, MIGNOT D (eds). Economica, Paris, 2010
VAHIDNIA F, WALSH J. Cost-Effectiveness of traffic Safety interventions in the United-States. Trafic
Safety Center, Institute of transportation Studies, University of California, Berkeley 2002, Research
Report, 22p
VAILLANT N, DERVAUX B. Les apports de l’économie de la santé à l’analyse des enjeux en sécurité
routière. In: Pour une économie de la sécurité routière. CARNIS L, MIGNOT D (eds). Economica,
Paris, 2010
WHITE KM, HYDE MK, WALSH SP, WATSON B. Mobile phone use while driving: An investigation
of the beliefs influencing drivers’ hand free and hand-help mobile phone use. Transportation Research
Part F 2010, 13: 9-20
Collective Expert Report
- 122 -
13/12/2011
WIJNEN W, WESEMANN P. BLAEIJ (de) A. Valuation of road effects in cost-benefit analysis.
Evaluation and Program Planning 2009, 32: 326-331
Collective Expert Report
- 123 -
13/12/2011
Collective Expert Report
- 124 -
13/12/2011
Summary
The mobile mobile phone and its non-voice applications have become very widespread
means of communication in all situations of daily life, including that of driving an
automobile.
However, automobile driving is a complex task that mobilizes perceptive, motor and
cognitive capacities. From a cognitive standpoint, the driver must select, from among the
many pieces of information coming from the road environment, those which are pertinent
for the task of driving, in order to make decisions and perform the actions that are adapted
to this situation. Telephoning while driving is likely to interfere with the activities of driving
and consequently, disturb the attentional capacities and degrade driving performance. These
disturbances were identified within the framework of experiments on driving simulators as
well as in actual situations with vehicles equipped with observations systems.
Because it can distract the driver, a mobile phone communication constitutes a risk for an
accident. The estimation of this risk requires evaluating, through epidemiological studies, the
influence of mobile phone use while driving on the risk of an accident. In order to calculate
the share of accidents that would be attributable to this usage, it is necessary to know the
frequency of mobile mobile phone use during driving as well as its duration.
In most accidents, several human and contextual factors act interactively in order to provoke
a dysfunction in driving. The respective contribution of these factors is difficult to isolate in
accident mechanisms. Although we can measure manner the participation of certain factors
in accidents such as alcohol or drugs in a relatively reliable, the same does not apply to other
factors such as the mobile phone.
In order to better target road prevention, knowledge of the various profiles of mobile mobile
phone users while driving as well as their motivation and the circumstances for this usage is
important.
At the beginning of the 2000's, France, like most countries, did not opt for a ban on the use of
the mobile phone while driving, but for a ban on hand-held mobile phones. A few studies
have evaluated this regulation, whether in terms of the impact on driving behaviors or the
socioeconomic impact.
Collective Expert Report
- 125 -
13/12/2011
In France, nearly half of all drivers use a mobile phone while driving
As noted in the AFSSET expert report 11 , "mobile telephony is marked by a distribution that is
massive, rapid and worldwide". The development began in France in 1997 with a sharp
increase until 2001. The increase in the number of users then continued at a lesser sustained
rate.
In 2008, nearly 80% of the French had a cell mobile phone. In June 2009, ARCEP 12 put forth
the figure of 58.9 million subscribers to mobile telephony in France.
Change in the number of SIM cards in France (in millions) (according to Idate Consulting
and Research, 2009, ARCEP data)
The mobile mobile phone and its non-voice applications have become a universal method of
communication regardless of the location.
The arrival of cell telephony (called third generation), which makes possible transmission
rates much higher than those of the previous standards (GSM: 2nd generation), has opened
the door to a very large number of applications, in particular the transmission of information
other than via voice. As such, the number of SMS (short message service) messages exchanged
in France more than doubles between 2006 and 2008: 34,396 million SMS messages were
exchanged in 2008 according to ARCEP.
For most people, the time spent in transportation including that spent in cars represents time
considered as lost, which a mobile phone communication makes it possible to "valorize".
Two methods make it possible to determine the prevalence of mobile phone use while
driving. The first consists in observation at strategic road points (these are often intersections
which force drivers to slow down and as such facilitates observation): a survey taken notes
whether or not a cell phone is in use for each of the vehicle drivers passing in front of him.
This is an instant evaluation of the prevalence 13 of use of the hand-held mobile phone, as it is
indeed much more difficult to determine from the exterior and without error the use of a
hands-free kit. These studies have very little precision as to characterizing the populations
studied.
11 AFSSET. Radiofrequencies: update to the expertise pertaining to radiofrequencies. Scientific edition from AFSSET. Physical
agents. Maisons Alfort, October 2009
12
The French regulator of the electronic communications and postal sectors
13
Instant prevalence measures the usage rate of cell phones in drivers circulating at a given moment.
Collective Expert Report
- 126 -
13/12/2011
The second method method uses surveys on the patterns of use, based on random samples
(general or specific surveys on mobile mobile phones, a survey that is more oriented on
mobility or on road safety): this entails knowing the percentage of subjects that use mobile
mobile phones while driving and to better characterize these users. This type of survey
makes it possible to take a much wider inventory of all of the types of mobile phone use, or
of other on-board equipment.
Carried out primarily in the United States between 2001 and 2008, the prevalence studies
give instant prevalence rates ranging from 3% to 6% (doubling of the rate over the last few
years). The rate of mobile mobile phone use is identical for day driving and for night driving.
On the other hand, there is a difference in terms of gender: young women use the cell phone
much more during night driving (12%) than men do (7.5%).
Studies carried out in Europe indicate prevalence rates that are slightly lower: in the United
Kingdom in 2005, the rate was 1.2% for hand-held mobile phones and 1.9% for hands-free
mobile phone kits; in Italy in 2006, it was 1.8% for hand-held mobile phones.
In France, the National interministerial observatory for road safety (ONISR) estimated that
the instant prevalence of mobile phone use in France was around 2.4% in 2006. A prevalence
of the same magnitude for hand-held mobile phones (1.8% for hand-held mobile phones and
earpieces and 0.5% for hand-held mobile phones) was found in the counting/observation of
the traffic carried out in 2009 on four types of roads (bypasses, rural highways, national or
regional roads in the open country, built-up areas
As for usage habits, several French studies show that one driver out of three to one driver
out of two are users, at least occasionally, of their cell mobile phone while driving. According
to the National interministerial observatory for road safety 14 , 10% of drivers report using it
often or very often. These studies already date back to 2006 for the most recent ones.
Note that there is almost no data concerning mobile phone use for drivers of two-wheeled
vehicles or bicycles.
The duration of communications (voice or via SMS) is an essential piece of data in evaluating
the risk, as it represents the exposure time of a driver to the risk of an accident due to the
mobile phone. The duration of communications depends in part on the daily driving time of
the subjects. As such, in Sweden it was in 2004 23 minutes for drivers of semi-trailers,
12 minutes for drivers of medium-haul freight trucks, 7 to 9 minutes for taxi drives and 7
minutes for private individuals.
The young, men and users of the road on a professional basis are those who
mobile phone the most while driving
Most studies have identified a high prevalence for mobile mobile phone use during driving,
in the young, in particular pertaining to the sending and receiving of SMS messages. This
primarily concerns the age class of drivers under the age of 35 years.
Mobile mobile phone users are most frequently men. In 2003, a French study indicated that
40% of men and 23% of women (all ages taken as a whole) mobile phoned while driving,
with this proportion decreasing with age in both groups. Nevertheless during night driving,
mobile phone use while driving seems higher in young women than in men.
14 Report of the Observatoire nationale interministériel de sécurité routière (ONISR) of 28 March 2007: cell mobile phones while
driving.
Collective Expert Report
- 127 -
13/12/2011
Several studies on the behavior of road professionals have made it possible to estimate the
prevalence of cell mobile phone use while driving and to reveal certain characteristics of
these behaviors.
As such, 99% of Danish professional drivers use a mobile mobile phone while driving, more
than 40% use the hand-held mobile phone, more than 50% answer calls regardless of the
circumstances, 50% never stop when they are making a call, 36% stop less than one time out
of two, 45% send SMS messages while they are driving. For 63% of these road professionals,
the mobile phone calls are of a professional nature in more than 90% of the cases.
In France, a 2007 survey gives an instant prevalence rate of 3.4% for drivers of light duty
vehicles, with cell mobile phones being used primarily during travel on highways and in
built-up areas. According to this same survey, the instant prevalence rate was 2.6% in drivers
of heavy trucks, with usage primarily on distribution and section roads (roads and
highways) and practically never in built-up areas.
Telephoning reduces the attentional resources available for driving
Automobile driving is a complex task that requires perceptive, motor and cognitive
capacities. From a cognitive standpoint, the driver must select, from among the many pieces
of information coming from the road situation, those which are pertinent for the road task,
and then he must respond with actions that are adapted to this situation.
In order to include the information processing mechanisms, cognitive psychology has
developed theories or models of cognitive operation. These models are based on data
concerning the observation of behaviors of people in experimental situations that make it
possible to control the environmental factors.
One of the characteristics with attention is the capacity to select the pertinent information for
an action in progress. In the preliminary research on the notion of selectivity, the information
processing system was designed as a filter with which only a single piece of information
passed at a time. Later research showed that this notion of a single channel for information
processing had to be widely nuanced.
A second major notion in understanding the phenomena of attention is the limited capacity
of the information processing system. There is apparently a central processor of which the
role would be to assign the attention to the various elements of the perceptive situation. The
capacity of this processor is limited, but flexible according to the intentions of the person,
motivational factors and their biological state. Certain tasks require more attentional
resources than others; they require more "mental effort". These are the tasks that involve
controlled processes, as opposed to automatic processes.
A controlled process demands a lot of attentional capacity, it is slow and of a serial nature
(one input is processed at a time). It is conscious, easily modifiable by the subject and is
affected by the other processing demands that occur at the same time. An automatic process,
on the contrary, demands few attentional capacities, it is rapid and parallel (several inputs
can be processed at the same time). It is not conscious, difficult to modify or suppress and is
hardly affected by other processing demands that occur at the same time.
The automatic processes correspond to routines that are acquired through repetition of the
same task. The distinction between automatic and controlled processes is important. It makes
it possible to include how certain routines can take place with little intervention of the
conscience and attentional resources. Automatic and controlled processes show two
Collective Expert Report
- 128 -
13/12/2011
extremes of a continuum, and can be involved simultaneously in complex activities such as
driving a road vehicle.
When people have to perform two or more tasks at the same time, attention can be divided
between several elements in the situation. The interference between two tasks performed
simultaneously depends on the level of automaticity of each of the two tasks. If both tasks
call upon controlled processes, the negative interference is high on performance. It is limited
(less negative) if at least one of the two tasks calls upon automatic processes.
Research has shown that the interference between the tasks depends on the sensory inputs
used. Negative interference on performance is higher if the two tasks use the same sensory
input, for example visual input.
By taking into account the current models on attention and the research carried out in
cognitive psychology on dual tasking, it can be predicted that the secondary "mobile phone"
task will interfere with the main "driving" task in two different ways:
•
when both tasks call upon the same sensory module. As the driving task always
has a visual component, having to turn away to look at the mobile phone, for
example to compose an SMS, should be more detrimental than a mobile phone
task using solely the auditive or vocal channel;
•
when one of the two tasks, even both of them, requires the recruiting of attentional
resources.
The availability of attentional resources depends on a certain number of characteristics of the
driver, such as his driving expertise, his cerebral state, his state of alertness or vigilance, his
state of cognitive fatigue.
Being an expert drive should facilitate the dual task: expert drivers have more automatic
functions and routines in order to handle the road situation; consequently, they need fewer
attentional resources in many conditions.
The existence of individual differences in the availability of attentional resources must be
underlined. Par example, the dual tasking is more difficult in the elderly and it is even more
difficult for people with a neurological disease.
Moreover, running out of attentional resources leads to a state of cognitive fatigue. The same
driver can have attentional resources at the beginning of a journey, but these resources can
decrease rapidly in a context of heavy traffic.
The question may be asked as to whether the attention theories developed on experimental
situations that are relatively "refined" can take into account the task of driving, which is
much more complex, in actual situations.
Certain studies have defined a hierarchy in the decision-making mechanisms of the driver in
actual situations. The decisions can be strategic (for example on the time of departure and
the itinerary), tactical (maneuvers) and operational (execution), with these three levels of
decision involving very different time scales. Other research has underlined that the driving
situation is not only complex, but also dynamic, bringing motivation and risk management
into the picture. This is how automobile driving models were developed that call upon the
notions of homeostasis and compensation for the risk, conscious of the situation and
avoidance of mental effort.
According to certain theories, the driver would apply the law of least effort with regards to
recruiting attentional resources: he would tend to favor the use of routines and the means of
reducing the mental load of the driving activity, by slowing down for example. As such, the
Collective Expert Report
- 129 -
13/12/2011
increase in the mental effort linked to mobile phone use while driving should result in an
adjustment of the vehicle's speed.
Future research should make it possible to determine whether drivers adjust and adapt their
driving when they are telephoning, in such a way as to not cause an overflow of the
attentional resources available. They will also make it possible to include whether or not
individual differences exist in implementing these behavioral adjustments, linked for
example to age, driving experience, sex or the personality of drivers.
Telephoning disturbs the driving activity
Many researches have shown the importance of selecting and processing information while
driving. Looking in the wrong direction at a critical moment and/or not seeing a critical
element in the road environment is not without consequences when you are driving.
Experimental studies have shown that the driver’s visual behavior is modified when they are
conversing on the mobile phone: they look straight ahead more, focusing on the central zone
of the road and neglecting to check the peripheral field, in particular the rear-view mirrors
and the control instruments. This phenomenon reveals an alteration in the visual information
processing which could indicate that when they are phoning, drivers give priority to the task
of navigating, to the detriment of other components in the driving task, such as scanning the
road environment.
A significant drop in detection performance is also observed. Phoning while driving
decreases the driver's conscience with regards to important information in the road scene,
which has the consequence for example of not seeing an object even if he is looking directly
at it ("look but fail to see"). This is linked to diverted attention to a context other than that of
driving. In other words, conversing on the mobile phone while driving affects the way in
which drivers pay attention to the elements in the driving environment. The capacity of
perceiving changes in the visual environment, which is essential for safe driving, is also
altered.
In the studies that attempted to measure the alteration of driving performance during a
mobile phone conversation, two main families of variables are more particularly studied:
driver reaction time to various types of signals, it is here that we find the most numerous
studies, and the parameters that make it possible to describe the vehicle dynamics, such as
lateral control, following distances and speed variations. The studies carried out in this area
have also attempted to demonstrate the possibility of adaptation behaviors of drivers:
increase in following distances, reduction in speed, but the results that were obtained are
diverging.
The results of meta-analyses show unquestionably that the drivers’ reaction time increases
when they are maintaining a conversation while driving. The alteration of the information
processing for the road environment could also have an effect on braking behavior for
drivers who brake with a delay and compensate by more abrupt braking when this is
necessary.
According to the meta-analyses, conversing on the mobile phone does not substantially
affect the lateral control or following distances. Note however that the studies taken into
account are not very numerous and are sometimes contradictory. Nevertheless, the fact that
the impact of the mobile phone is expressed rather in terms of an increase in response time
rather than in terms of lateral control, could be explained in the sense that the latter takes
place relatively automatically and requires few attentional resources, contrary to responding
to an unexpected signal which requires not only detecting this signal, but also selecting a
Collective Expert Report
- 130 -
13/12/2011
sequence of actions that are appropriate in order to respond to it. Some studies have even
shown that lateral control could be improved during mobile phone communications. Indeed,
controlling the trajectory is highly linked to where one is looking. The gaze concentration
towards the center of the lane observed when drivers are performing cognitive tasks could as
such result, in certain cases, in a better maintaining of the vehicle in the lane.
The few studies that have addressed the effects of mobile phone use on decision making
have shown that a mobile phone communication could alter a driver's judgment capabilities
or his ability to make certain decisions. Drivers would as such avoid performing certain subtasks in driving that are more secondary, such as changing lanes, and would favor
maintaining their trajectory. This avoidance behavior, sometimes accompanied by a higher
number of errors and violations, is in favor of an alteration in the situation awareness of
drivers, who can no longer process all of the information in the road environment. Mobile
phone conversations would also further affect drivers in situations that require making a
complex decision, such as making a left turn, and less in situations where making decisions
is simpler, such as stopping at a red light.
Various studies have tried to compare the respective effects on the driving behavior, of
conversations initiated with a hand-held phone and a "hands-free" phone. It is shown that
these effects are not very different, indeed, the response times increase in an equivalent way
whether or not the phone is hands-free or held in the hand.
It is in terms of speed that the differences are the greatest with the obtaining of a decrease in
speed when the mobile phone is hand-held. This decrease in speed could correspond to an
adaptation of driving behavior aimed at reducing the additional mental workload generated
by telephoning and holding the phone, in order to maintain it at an acceptable level. Drivers
could also have increased awareness of the negative effects on driving of a distraction
generated by a manual task, such as holding the phone in the hand, and underestimating this
distraction if it is purely cognitive with a hands-free phone. The negative impact of the handheld phone could however be made worse in situations that require manual intervention
from the driver (turning in an intersection, for example). As such, even if it is likely that the
hands-free phone can be advantageous in certain situations, it is clear that it cannot resolve
all of the attentional problems linked with using mobile phones while driving.
Using a mobile phone implies not only maintaining a conversation, but also performing
different tasks of a visual-manual nature, such as dialing, picking up/hanging up, reading or
writing SMS messages, etc. These tasks will obviously not have the same effects on driving
as that of conversing, of a verbal and auditive nature.
First of all, the increase in response times to an event recorded during mobile phone
conversations increases during the performing of visual-manual tasks. The latter induce a
diverting of attention towards the interior of the vehicle, thus resulting in a momentary
interruption in the processing of information coming from the road environment. As lateral
control is highly linked to the direction where one is looking, the position on the road is
degraded. Finally, in order to overcome an intermittent control of the environment, drivers
strive to maintain an acceptable trajectory by reducing their speed or by making corrections
with the steering wheel. Moreover, holding and/or manipulating a mobile phone or
keyboard requires the use of a hand, which can also generate a biomechanical interference
with the holding of the steering wheel and add to the difficulties of controlling the trajectory.
The question of knowing whether or not it is more dangerous to be speaking on the mobile
phone or with a passenger is still up for debate. The meta-analyses show a similar cost for
the two types of communication on driving performance (response time and vehicle
dynamics). However, the studies retained in these meta-analyses are very few and provide
opinions that are sometimes diverging; these results are therefore to be interpreted with
Collective Expert Report
- 131 -
13/12/2011
precaution. Several studies on a simulator have in particular shown that there is a higher
number of driving errors (navigation errors, for example), incidents or accidents during
mobile phone conversations compared to conversations with a passenger. The authors
conclude from this that phone conversations would require more attentional resources from
the driver, and would therefore be more detrimental to driving.
The quality of the speech was analyzed in order to obtain a better understanding of these
differences. A degradation is observed for mobile phone conversations while driving
compared to conversations with a passenger (in terms of fluency, hesitations and repetitions)
and would reveal a higher attentional demand. First of all, the fact that the person being
spoken to is not present requires additional cognitive resources from the driver who tries to
compensate the absence of non-verbal feedback that is specific to face-to-face
communication. Then, a mobile phone conversation is characterized by a requirement for
continuity, as silence could potentially be misinterpreted by the other party. Finally, the
absence of information on the surrounding traffic for the callers prevents them from being
able to adapt their cooperation according to the driving conditions. Communication with a
passenger could as such be modulated or interrupted momentarily when the additional
driving demand increases, which is less obvious with phone conversation.
The effect of mobile phone conversations was also compared to that of listening to various
types of verbal material, such as the radio. It has been shown that tasks limited to listening to
information that is not personalized and that is not interactive do not affect visual behavior
or the driver's reaction time. Indeed, listening to vocal material is not enough, per se, to
generate interference with the driving task. In the absence of a genuine engagement in a
verbal activity, which is generally the case when listening to the radio, no degradation is
observed. Indeed, the interference observed during phone conversations is not located at the
motor level of language production, but on the level of the cognitive processes that are
required when carrying on a discussion. Of course, the additional demand could vary
according to the material being listened to and if it is differentiated from manipulating the
controls of the radio.
Accidents are a failure in terms of the interaction between the driver and his
environment
The question of human factors in the research of the causes of accidents is a subject that is
complicated as well as recurring in the field of road safety. The notion of "human factors"
refers to all of the variables linked to the person which are likely to have an incidence on
driving behavior and on the occurrence of an accident. This includes demographic variables
such as age and sex, physiological variables such as fatigue and alcohol intoxication,
psychological variables such as inattention or distraction, attitudinal variables such as risk
taking, etc. going as far as to encompass the results of all of these variables which are human
errors (perception, evaluation, action, etc.).
The contribution of such factors is far from being easy to isolate in accident mechanisms.
This can be explained by the fact that, as has been indicated in much research works in the
field of ergonomic psychology, in complex systems such as car driving, the origin of the
problems resides much more massively in inappropriate interactions between the various
components in the system than in the exclusive characteristics of one of the components. In
most accidents, different human and contextual factors act together, provoking a
dysfunction, whereas taken separately they would not have generated any difficulty. This
therefore entails keeping the relative nature of the involvement of such and such identified
Collective Expert Report
- 132 -
13/12/2011
factor in mind. It also entails not confusing human error with the factors (human and
contextual) that produced it; otherwise the effects and their causes would be mixed together.
For some factors, such as alcohol and drugs, relatively reliable measurements of the
participation in driving defects are available. But for most of the human factors, statistical
data on accidents is based on reports established by police services according to the
information that they can collect within the framework of establishing their procedure. A
precise analysis of the difficulties that drivers are exposed to in certain driving situations and
the cognitive processes that are incriminated in these difficulties would make it possible to
characterize the attentional failures of which certain accidents bring to light.
In terms of road safety, we are now seeing more awareness of the attentional problems while
driving. However, from a conceptual standpoint, literature still contains terminological
nuances on what is meant by attention, distraction, inattention, etc.
The concepts used vary from one author to another, with very different definitions and
which cover diverse processes. Such a conceptual heterogeneity brings great variability in
the data which is supposed to characterize the causes of accidents. As such, the occurrence of
vigilance problems in accidents varies from 1.8% to 54% according to the studies, and
attentional problems from 25.6% to 78%. This forms a range of data that is much too
scattered to provide the slightest useful indication. There is therefore a need to correctly
distinguish the processes that the concepts used include.
A preliminary distinction must be established between: 1) what stems from a problem of
vigilance, which qualifies the non specific activation processes of the organism, and 2) what
corresponds to a problem of attention, designating the processes that condition the
orientation of the cognitive resources allowing for the specific processing of information. The
disturbances of these two sets of processes show very marked differences in the genesis of
accidents. However, the problems of vigilance and attention are very often confused in
accident data.
Closely tied to the very high variability of road situations, attentional disturbances form
complex and sometimes contradictory problems, and their sources are multiple. As such, in
an actual driving situation, the driver is constantly dividing out his resources between all of
the potential sources of stimulation, as the attentional capacities, by definition, are limited.
The driver cannot remain 100% focused on the task of driving; otherwise he will exhaust
himself quickly. There is a "cognitive compromise" between the requirements of the task
(adaptation to the rules, safety, performance) and the interests of the biological system (limit
the cognitive cost). Attentional control therefore makes it possible to assign, in a way that is
most often adapted, over time and in space, the resources that are required for each of these
components. The attentional problem occurs either when the resources assigned to the task
become insufficient in relation to the requirements of the task, or when the driver focuses on
a portion of the situation that is too restricted to solve the problem. As such, it is the
imbalance in distributing out the resources between the various sources of information,
relative to their requirements and priorities, which leads to the various attentional failures.
The dispersion of attentional resources can be synonymous with cognitive economy, and
therefore effectiveness over time. It has the potential of becoming the cause of accidents only
in certain situations that it is important to accurately define. The improvement in knowledge
on the operator's cognitive operation and the difficulties that he encounters in his activity of
travel should as such make it possible to adapt the travel environment to his capacities in
order to make the overall system safer.
The amount of research concerning the impact of mobile telephones on driver performance
has not stopped increasing since the end of the 1990's. Today, the telephone is not used solely
for conversation. All of the operations linked to telephone use that will involve a
Collective Expert Report
- 133 -
13/12/2011
mobilization of all attentional resources (cognitive, visual, motor) will have an increased
power of degradation, not only on interaction with traffic, but also on regulating the
trajectory, as automated as it is. Two types of distractions potentially generated by the
telephone can be distinguished: a "purely cognitive" distraction, which corresponds to the
period of conversation; and an "integral" distraction which corresponds to all of the
operations during which the diversion of attention is accompanied by a diversion of the
operator's look off the road scene (looking for the telephone or its accessories, dialing a
number, writing/reading a message, etc.).
Any source of distraction is potentially harmful from a driving standpoint, combined with
the complexity of the situations experienced, the multitude of variables to be processed and
the consecutive solicitation of the individual's attentional resources. Due to the dynamics
and time constraints which characterize it, the variability of the situations that are possible,
the profusion of information to be handled, or on the contrary the monotony of certain
situations, driving an automobile is an unparalleled revelation of the attentional difficulties
put on the human being in his attempts to adapt to the activities with which he is confronted.
And accidents bear witness to all of the limits of these capacities to adapt, which must not be
pushed to the end through confrontation with unnecessarily complicated infrastructures,
poorly-presented information, excessive traffic speeds… anything that increases the
additional load.
In France, nearly one road accident out of ten is associated with mobile
phone use while driving
Experimental studies show that telephoning while driving disturbs driving activity.
Does this disturbance result in an increased risk of an accident in actual driving situations on
the road network? In other words, does the fact that some drivers mobile phone while
driving lead to a certain number of accidents?
In order to answer the question, drivers would ideally need to be observed behind the wheel,
their mobile phone use, and count the accidents that they are involved in. A few studies
carried out over several tens of vehicles equipped with multiples sensors, in particular visual
sensors, and followed for one year, did not make it possible to obtain reliable estimations of
risk, due to the "rather" low number of accidents recorded.
Among the epidemiological studies for the general population which evaluated the influence
of mobile phone use while driving on the risk of an accident, only ten studies published in
international literature in the last fifteen years deemed that the quality was sufficient to
allow an evaluation to be carried out. This rather low number can be explained by the
difficulty in obtaining pertinent information on sufficiently-sized samples.
The diversity of the epidemiological approaches used prevents estimating an average risk
regrouping the various studies via meta-analysis techniques. However, these studies can be
classified into two groups: those that have tried to estimate the risk of a specific accident
linked to the action of telephoning, and those that have compared the rates of accidents of
mobile phone users while driving to non-users, without trying to know if the people were
actually telephoning at the time of the accident.
The difficulty in the studies of the second group is to characterize the effect itself on the risk
of an accident of a more or less frequent use of the mobile phone while driving, although
mobile phone users are surely different from non-users in terms of many points such as their
travels and their behaviors on the road. That is why we have retained only studies that
Collective Expert Report
- 134 -
13/12/2011
present risk estimations that are adjusted for a certain number of factors such as age, sex and
the distance travelled. It can be retained that the additional estimated risk (called the relative
risk) of an accident combined with the possibility of telephoning while driving is between
1.10 and 1.20, keeping in mind that this is an average value for all drivers who use their
mobile phone while driving. The only study carried out recently in France provides
additional precision by distinguishing, on the one hand, drivers who declare that they use
the mobile phone while driving only when the driving conditions allow for this and on the
other hand, drivers declaring that they use it regardless of the circumstances. The relative
risk associated with the latter compared to non-users is 1.7, but, concerns less than 10% of
mobile phone users. If we consider that the first group do not have a significant increase in
the risk of an accident in relation to non-users, the value of the relative risk associated with
all mobile phone users, i.e. 1.7x10%+1x90%, or 1.07, can be taken to be of the same order of
magnitude than as in the studies which have calculated an average value for all of the
drivers who occasionally mobile phone while driving.
The other selected studies feel that the risk of an accident for driver in the process of
telephoning in relation to a driver who is not telephoning. Among the latter, two use the
study structure referred to as "case crossover", which entails comparing for the same driver,
mobile phone use over a short period of time preceding the accident to a prior equivalent
period. This approach makes it possible to adjust the measures of association for most of the
"fixed" characteristics of drivers. The estimated relative risks are between 3 and 5 according
to the studies and sub-groups studied. The main bias linked to this type of study is the
attribution to the period preceding the accident of mobile phone calls that took place after
the accident, due to the lack of precision of the instant of the accident. This confusion leads to
even more consequences as all of the studies show that the number of calls after the accident
is very high. However, the selected studies exclude emergency calls and retain only those
subjects for which there is a coherency between the sources of information concerning the
instant of the accident. Above all, the relative risk attached to incoming calls is the same as
that attached to outgoing calls in the only study that provides this precision, which is a very
strong argument for thinking that this bias was avoided for a large part. Finally, the applied
method consists in comparing periods during which the driver made or received a call,
without being certain that the driver was still on the phone at the time of the accident. The
effect of this problem of incorrect classification probably results in an overestimation of the
risks, but the authors do not discuss the extent of this bias.
With a very different methodology based on comparing drivers estimated "at fault" or not "at
fault", another piece of research arrives at an estimation of the relative risk of 2.4 which is
without a doubt an under-estimation in light of the method used.
As such, primarily using "case crossover" studies, the choice of a value for the relative risk of
around 3 seems reasonable for the rest of the calculations.
Since the various studies provide results that are close, whether entailing considering the
occurrence of damage or bodily injury accidents, the risks of being involved in a personal
injury or damage accident according to whether or not one is telephoning while driving will
not be distinguished.
Moreover, no epidemiological study shows a significant difference between the risk
associated with the hand-held mobile phone and that associated with hands-free systems,
without a distinction of the type of system. It can be noted that, in these studies, hand-held
mobile phones represent a risk that is always higher, but not enough to show a difference
that is statistically significant.
A few studies done on vehicle fleets equipped with sensors recording the various behaviors
of drivers show, as the primary result, a prioritization of the elements causing distraction
Collective Expert Report
- 135 -
13/12/2011
and inattention while driving, among which is the mobile phone. The relatively reduced
number of equipped vehicles and the monitoring time do not however make it possible to
study the risk of an accident, but rather the risk of potentially dangerous activities. These
studies seem to indicate a higher risk associated in the dialing of a number on a hand-held
mobile phone, which is very coherent with the results of the experimental studies.
Finally, two estimations of relative risks can be retained. The first between 1.1 and 1.2
represents the average risk of an accident for a driver likely to mobile phone while driving,
in other words telephoning during a portion of his driving time. The second estimation,
around 3, represents the risk of being involved in a damage or bodily injury accident for a
driver in the process of telephoning in relation to a driver who is not telephoning, and this
regardless of the system used (hands-free or not). This is the additional risk taken by the
driver when he is having a mobile phone conversation in his vehicle. Then, it is important to
know what proportion of his travels is concerned with this increase in risk.
According to the survey taken in France in 2007, about 2.4% of drivers were seen holding a
mobile phone in their hand. Knowing that the hand-held mobile phone represent more than
40% of mobile phone use while driving, it can be estimated at 6% the prevalence of mobile
phone use while driving (hand-held and hands-free), by making the hypothesis that the
communication times are, on the average, depend little on the system used.
As such, for a given journey, a driver mobile phone on the average 6% of the travel time, and
during this time his risk is multiplied by 3, and for the remaining 94% of the time, he is at the
basic risk. In other words, his average relative risk is 3x6%+1x94%, or 1.1, which is the value
found for the relative risk associated with mobile phone owners. If we take the high values,
with a driver who mobile phones 10% of the journey and a relative risk of 4, we obtain 1.3.
With these values of prevalence estimated in France, the determinations of risks according to
the two types of studies, beyond all of their differences, seem highly coherent.
An attributable risk can also be estimated, in other words the proportion of accidents
associated with mobile phone use. With the values of 6% for the prevalence and 3 for the
relative risk, we obtain an attributable risk equal to 10.5%. Making the calculation this time
using 1.2 for the risk associated with a mobile phone owner and 44% for the corresponding
prevalence, the attributable risk is 8.1%. In other words, using diverse estimations
considered to be valid, the proportion of accidents (damage or bodily injury) associated with
mobile phone use while driving is estimated to be about 10%.
Drivers poorly assess the risk that they take when phoning while driving
Several authors have taken an interest in the perception that drivers have of the risk
associated with phone use while driving. This is how phoning while driving was compared,
within the framework of the European Sartre survey, to a series of possible causes of road
accidents linked to the state of the driver, the state of the vehicle or the traffic conditions. The
drivers surveyed felt that phoning while driving, whether or not hand-held, as behaviour at
low risk yet having a strong prevalence in the case of the hand-held phone.
The risk linked to phoning while driving was also compared to the risks generated by
different activities that drivers can be led to perform while driving. The risk is perceived
differently according to the type of phone. Conversing with a hands-free phone is judged as
an activity with much less risk than conversing with a hand-held phone. Because, among all
of the situations of driver’s distraction linked to multi-activity while driving, it is driver’s
distraction induced by visual-manual interactions which are judged as those with the most
risk. The cognitive distraction linked to phone conversation is under-estimated. This
Collective Expert Report
- 136 -
13/12/2011
observation is confirmed when surveying drivers on the different actions that they can
perform with their cell phone. Writing and reading an SMS, dialling a number, manipulating
the keyboard and reading the screen are judged as the actions with the most risk.
From this casework, we see that the perception of the risk linked to phone use while driving
varies according to whether or not the drivers declare that they phone while driving, with
non-users judging the risk higher than users do. There are also differences within the
population of drivers declaring that they phone while driving. Drivers who phone the most
frequently while driving and systematically (i.e. who call and answer the phone regardless of
the driving context) have a lesser degree of awareness of the risk taken, while the proportion
of people declaring having been confronted with risky situations while phoning during
driving increases with the frequency of phone use while driving. The most often mentioned
critical situations are moments of inattention when following a vehicle, deviations in
trajectory, not seeing traffic signs and dropping the speed to the point of disturbing other
drivers. Finally, drivers who use a hands-free kit have a high frequency of phone use while
driving and a perception of the risk taken when phoning while driving that is higher than
drivers that are not equipped. This can explain their choice of installing a hands-free kit in
order to continue their practice with a maximum degree of safety and avoiding a ticket.
Among all of the risks linked with mobile telephony, the one linked to cell phone use while
driving appears to be a familiar risk that drivers freely choose to take as they draw an
advantage from it and they believe they control it. The risk of an accident is judged as severe
(the effects of phoning on driving are not considered as negligible), inequitable (those who
phone while driving are not a risk just to themselves) and probable (those surveyed would
need little convincing that phoning while driving was dangerous). Finally, several authors
have identified an "optimism bias" in terms of the perception of the risk of accidents linked
to phone use while driving: the risk of an accident is deemed higher for others than for
oneself.
Although the perception of the risk of an accident and tickets does exist in the majority of
drivers, it is not however enough to counterbalance the advantages that are afforded by the
cell phone and the social pressure from others to use it while driving.
Better knowledge of the underlying factors influencing the driver's intention to initiate or not
initiate the use of a cell phone while driving seems to be an interesting path in order to better
target future regular public awareness campaigns on the risk of phoning while driving.
In most countries, institutional responses are rarely evaluated, centered on
the driver and are primarily of a regulatory nature
The Order no. 2003-293 of March 31, 2003 banned "the use of a hand-held mobile phone by
the driver of a vehicle in circulation". Driving with a mobile phone in their hand, a driver is,
in France, risks a lump-sum fine of €35 and 2 points off their driving license. Measures of this
type have been taken by almost all of the governments of the European Union and by other
countries with similar conditions of life.
Recourse to law is a privileged solution in most countries. It is based on the hopes of
modifying the driver's behavior. Two types of laws exist. Laws of a general nature allow law
enforcement officials to reprimand and sanction driving that they feel is dangerous. Yet,
around the years 1990-2000, most governments opted for specific regulations, i.e. explicitly
treating mobile phone use while driving. Within this framework, the vast majority of
countries have opted not for a ban on mobile phone use while driving but, like in France, a
ban on hand-held mobile phones.
Collective Expert Report
- 137 -
13/12/2011
The main variants, from one country to another, concern the sanction, i.e. the amount of the
fine and whether or not there are also penalty points. The sanction can vary over time, with
the example of the stiffening of the English text in 2007. A more precise analysis indicates
that usage restrictions exist or are being considered (according to the type of device, the
duration of the call and the location of use), bans targeted to certain populations (young
drivers in some American) and exceptions to the general framework (for certain professions,
for example).
These various recourses to law do however raise the question of controlling it and the
effectiveness of the sanction. One of the main critiques made in extending the ban to handsfree kits resides as such in the difficulty for law enforcement officials to detect these
practices, unless they are provided with technological tools which allow for this or unless
they can massively stop drivers. "Hands-free" laws however are also perceived as being
difficult to apply and in particular at night or for vehicles equipped with tinted windows.
The attitude of judges and law enforcement officials with regards to this violation can also
vary substantially from one jurisdiction to another.
Yet, recourse to law can involve stakeholders other than the driver. A requirement
concerning construction standards can be considered (for manufacturers of automobiles and
telephony devices) as well as certain obligations for professions. The main ones are
mandatory information on the dangers of use, required of car rental companies, and a
systematic collection, by law enforcement, of data on mobile phone use during an accident.
For example in Quebec, research recommends that automobile manufacturers be subjected to
standards aimed at restricting or in neutralizing the use of telematic devices while driving.
Other regulations (Great Britain) aim to increase awareness and further involve private
stakeholders. This entails encouraging, for example, initiatives from insurance companies
and employers in order to avoid or, if it is absolutely necessary, limit cell mobile phone use
by their employees.
Other public actions, which are not related to sanctions and repression, also exist. This
entails, for example, efforts on informing drivers and employers on the risk incurred when
telephoning while driving, which involves communication campaigns and education actions.
Of course, these measures are not used indifferently. The least restrictive measures
(communication) were in general followed by more restrictive ones (ban on use). The
measures taken in France and in England since the end of the 1990's are the perfect
illustration of this type of dynamics. Moreover, much research, not necessarily addressing
the mobile phone, has shown that the control via law enforcement officials must, in order to
be effective, be accompanied by communication campaigns.
Literature shows the many interrogations as to the pertinence and the effectiveness of the
measures that exist, in particular, because they appear to be "disconnected" from any
approach to analyzing and assessing public policy.
The laws adopted are now old – some are nearly ten years old – with regards to the rapid
development of communications technologies and highly expanding usage in certain user
categories. When these measures were adopted, few deaths could be attributed to mobile
phone use while driving, although pioneer research on the risk taken warned about the
dangers of this behavior.
Today, "hands-free" laws are denounced as incoherent in relation to the scientific results,
which show that "hands-free" devices do not prevent the cognitive distraction linked to
conversation. Therefore, the safety potential of these laws is deemed to be limited and
sometimes even, they are denounced as bearing perverse effects. They were sending an
incorrect safety-procuring message to drivers.
Collective Expert Report
- 138 -
13/12/2011
Has the research carried out, for 10 years, made it possible to sufficiently increase the
knowledge on this phenomenon and its impact on road safety assessments? Mobile phone
use while driving is still rarely documented in accident reports; the impact of the measures
taken on the behaviors of users has hardly been evaluated; reception of the repressive and
educational measures has not been measured. There is also little information on the
effectiveness of the repression on non-compliance with the regulations adopted. The rare
studies that exist indicate that the bans do not have a long-term effect on the behaviors and
have to be supported by control and communication. But, this research was for the most part
done in the Anglo-Saxon world. And, referring to studies carried out in another societal
context, or in another period of time, raises issues.
The actions developed by governments are based on a reduced view of the problem and of
its solution. The main measures, whether stemming from strategies of a repressive, educative
or communicational nature, offer solutions to the behavior judged as deviant of the driver.
Such a focal point tends to reduce the road safety approach to supervising and controlling
driving behavior. Mono-causal solutions are as such built and address isolated individuals.
Yet, the act of driving is an act that is situated and subjected to a multitude of constraints for
which it is also suitable to act for increased effectiveness of public action.
The analysis of the actions carried out in different countries (Western countries in particular)
underlines that regulations cannot be considered using a binary matrix (ban versus
authorization). The government can attack the road insafety problem by using its legal
powers, but also the information at its disposal, its financial resources and its organizational
capacities. Then, these instruments do not have for sole objective to change driver behavior.
They can be used to encourage other stakeholders to better take into account the stakes of
road safety that are inherent to mobile phone use while driving. Finally, these various
measures cannot be considered independently in relation to one another. Some suggest
reflecting on an action program in terms of the "integrated safety chain" which would allow
for the development of actions on vehicles and the infrastructures in a close relationship with
interventions aimed at changing the behavior of the users. The doubts expressed, in expert
literature, on the instruments used today lend support to the interest for such an approach.
In addition, the scientific results obtained are hardly discussed and in particular by the
diverse stakeholders interested in the use of telephony devices while driving. However, the
latter are extremely diverse. There is little or no convergence and little or no structured
thought from all of these stakeholders (public authorities, manufacturers, operators, experts,
insurers, employers, employees, etc.) of which the resources, interests, capacities for
mobilization are differentiated.
A process that is of an assessment nature as well as debatable is lacking to reach not
necessarily a co-decision but at least a co-interpretation of the results of the research work
which would allow for the development of an effective public action.
Literature underlines that several instruments available to governments can be mixed in
order to effectively fight the behaviors at risk and that there are tools making it possible to
accumulate scientific proof as to the effectiveness of the measures taken and those being
considered. In the same way, it suggests the pertinence of a participative assessment which
would bring together the various stakeholders. Gathering the opinion of the interest groups
involved can also make it possible to better situate the political debate and therefore a better
consideration of the possible consensuses in order to amend the legislation.
Collective Expert Report
- 139 -
13/12/2011
To date, the ban on telephoning while driving cannot be justified by the
socioeconomic data available
Performing a socioeconomic evaluation of road safety measures or more generally of a
measure or transportation policy supposes that all of the advantages and disadvantages
linked to the measure in question are taken into account and to assess these. The most
commonly used method of evaluation, in France as well as abroad, is the cost-benefit
analysis. This consists in carrying out an up-to-date assessment of the gains and losses linked
to a measure, for example the ban on telephoning while driving, for all of the stakeholders
involved (users, companies, the State or local authorities) and which takes into account all of
the monetary elements (financials) and elements that can be monetarized (time, safety, noise
and pollution).
As such, the analysis incorporates the following financial elements: the costs of the measure
or of the policy (for example, costs links to mobilizing the police forces for the control or the
cost of the information campaign); the financial gains or losses for the various stakeholders
(as such, a ban on the mobile phone would fully eliminate the costs and the gains of calls for
the users and the expenses of the health system, as well as the gains for garage owners,
certain employers and telephony operators, etc.).
The rare research carried out on assessing the measures taken to counter mobile phone use
while driving was carried out in the Anglo-Saxon countries (United States, Canada,
Australia). The issue of evaluating the practice linked to hands-free kits is very rarely
addressed as such in this research which simply includes the results of the behavioral studies
which do not show that a hands-free mobile phone is safer than a hand-held mobile phone.
Certain authors conclude however that a selective restriction of the hand-held mobile phone
yields lower costs and benefits but has the same cost-effectiveness ratio as a full ban on
telephoning while driving.
Moreover, this research refers to uses of the mobile phone which are rapidly changing, in
terms of volume as well as in terms of type of use. However, a certain amount of information
can be drawn from these studies and will make it possible to direct other research to be
carried out for France.
The first extensive study carried out in 1999 in the United States made it possible to say that
the ban, by reducing the number of accidents, would allow for gains of 1 million dollars a
day for the health system and 4 million a day for the other financial costs (insurance costs,
taxes, travel delays, material damages, etc.). On a comparable basis, another study in 2003
estimates these potential gains to be 35.7 billion dollars per year for the United States. A
more recent study (2009) in Canada (Alberta) incorporates the production losses linked to the
death of agents with the ability to produce into the calculation, estimated to be 90,000 dollars
per injured person and 2.7 million dollars per death.
These studies suppose that the incremental risk of an accident is proportional to the time
spent on the mobile phone. As such, for a driving time per day and per driver estimated to
be 60 minutes, the time spent on the mobile phone was estimated to be 2 minutes a day for
studies that were done at the beginning of the 2000's and 3.6 minutes minutes for the most
recent study in 2009. In all of these studies, the relative risk of an accident on the mobile
phone taken into consideration is an average of 4.3.
With regards to the valorization of the time spent on the mobile phone, the first study in the
United States (1999) made reference to a time value for users of $0.47 per minute, based on
the value of the demand for this type of services (i.e. the price of the communications).
Inversely, the financial cost of the calls for users was estimated to 0.38 dollars a minute for
studies concerning the United States.
Collective Expert Report
- 140 -
13/12/2011
In sum, the surplus for users, i.e. the difference between the value of the call and the cost of
the call for the user is estimated to be $0.09 per minute by the first study of the question in
1999 and at $340 per person per year on the average for the second study in 2003 in the
United States.
The social benefit of a measure to ban telephoning while driving resides in a decrease in the
number of deaths and injuries. It is therefore based on a valorization of human life and the
injured. As such a measure which makes it possible to prevent a death on the road in France
is valorized at 1 million euros (value in 2000), and €150,000 for a serious injury and €22,000
for a slight injury. This social benefit was as such estimated to be 43 billion dollars on the
average in 2003 for the United States.
In the end, the overall assessment of banning cell mobile phones while driving is estimated
at a cost per QALY (year of life in good health) of $300,000 in 1999, at an annual loss of
$23 billion estimated for the United States, or a negative net benefit of $220 million in 2003.
For the last study on Alberta, the estimation is that there is an 80% that a ban results in a gain
and a 94% chance that a ban costs less than $50,000 per QALY.
The assessments therefore differ somewhat according to these three studies. As such, for the
two American studies (1999, 2003) a banning of cell mobile phones is clearly not
economically efficient even with a more balanced for the study in 2003 (a negative net benefit
of $220 million is not a very high amount). The authors as such feel that restrictions on cell
phone use while driving have a lesser cost-effectiveness ratio for society than the other
measures in terms of safety (example of lateral airbags) or in other words there are actions
that could be more effective in terms of reducing accidents and at a lesser cost than banning
the cell phone. They do conclude however that drivers should avoid unnecessary calls, have
short conversations, and suspend the exchange in the event of dangerous circumstances (but
do not develop these any further) and that a ban for young drivers (who have the most
accidents) could be economically beneficial for society.
For the authors of the last study to date on Alberta (2009), a banning of cell mobile phones
while driving is potentially interesting in a society perspective. They show that the results
are sensitive to parameters for which there is very little information or for which the
information is contradictory. These authors also mention the question of a targeted ban for
young drivers who have the highest risk of accidents and consider that there is no
"economic" reason for banning the use of the mobile phone use while driving if the drivers
"assume" i.e. pay, for the damage caused.
In all of this research, the uncertainties and the biases are many and the results must
therefore be taken with precaution. But, all state that the final result in fact depends on a
single parameter which is the valorization of mobile phone calls, with the risk factor having
the least influence.
Concerning hands-free systems more particularly, if we hypothesize that the systems are
expensive and that they are intended for experienced drivers that have a lower risk of an
accident and a high valorization of time, in this case a ban would be even less economically
effective.
Several authors conclude that the question of the law is not only an economic question.
Indeed, the economic cost/effectiveness ratio for measures limiting mobile phone use while
driving depend above all on the value of the communications or on official values for human
life and the injured according to the methods used. This in fact ends up putting the question
of political responsibility back in the center, as the official values retained reflect only the
priorities that the authorities give to the question.
Collective Expert Report
- 141 -
13/12/2011
Collective Expert Report
- 142 -
13/12/2011
Recommendations
Mobile telephony has developed exponentially over the last decade as well as the
development of a multitude of functions associated with it. Its use in all situations of daily
life (professional, social or in a family context) is changing very rapidly. Surveys show that
the frequency of its use while driving varies according to the various factors such as sex, age,
and whether or not one is on the road for one's profession.
Many experimental studies have shown the decline in driving performance during a
telephone conversation, whether the telephone is hands-free or hand-held. This impaired
driving performance is particularly visible in terms of the increase in response time to an
event. This delay is even longer as the conversation is more complex. In comparison with a
conversation with a passenger, a telephone conversation would require more attentional
resources from the driver, and would therefore be detrimental to driving quality. Dialing,
reading or writing an SMS disturbs driving even more.
Moreover, epidemiological studies have made it possible to identify a multiplication of the
risk of an accident by a magnitude of three due to the use of a telephone while driving,
regardless of the system used (hands-free or not).
France, as almost all of the countries in the European Union, has banned the use of handheld
telephones while driving since 2003. Likewise, since 2008, "placing within the field of vision
of a driver of a vehicle in motion of a device that is operating with a screen and which does
not constitute assistance in driving or in navigation is banned". Yet, we are seeing a
diversification in the possibilities for using mobile telephony in a road vehicle using onboard systems or not and comprising a screen.
The impact of this legislation on the behaviors of users has not been documented much to
date in the countries involved. Likewise, little data exists on enforcement concerning noncompliance with these regulations.
Although it is not the duty of this group of experts to rule on the changes in regulations in
terms of using the telephone in driving situations, the recommendations carried out are
aimed at providing the best accompaniment to the public action, whether or not the law
changes quickly. These recommendations make it possible to suggest an improvement in the
knowledge of the relations between telephone use and the risk of road traffic crash and to
develop concrete measures incorporated into a program of actions.
As such, the change in the knowledge on the actual risk associated with the use of telematic
systems while driving, on the influence of distracting elements and possible compensation
strategies implemented by the drivers should result in a re-adaptation of road safety
measures. A coherent program of actions should take the following into consideration:
•
regulations, which could be necessary to change according to the knowledge on the
consequences in terms of road risk and the socioeconomic impacts of the new uses for
telematics;
•
the development of devices accompanying the on-board technologies, likely to
facilitate the application of regulations on the conditions for mobile phone use;
•
informing the public and training drivers on the risks associated with the use of the
hands-free system and other systems that are likely to act on behaviors during
driving.
Collective Expert Report
- 143 -
13/12/2011
The evaluation of the social and economic impact of the measures must make it possible to
adapt them and to redirect them on a regular basis like an "integrated chain of safety" within
the framework of the road safety policy.
Regulatory and technological measures
Since 2003, French legislation has banned "the use of a hand-held mobile phone by the driver
of a vehicle in motion". This ban can implicitly suggest that the use of a hands-free device
while driving is less dangerous as it is not banned.
Scientific results do not make it possible to differentiate between the two situations, although
holding the mobile phone in your hand does add a visual-manual distraction linked to the
manipulation of the mobile phone. Whether or not the mobile phone is held in the hand, the
risk linked to the cognitive distraction induced by a mobile phone conversation is
comparable (risk multiplied by a factor of a magnitude of 3).
Moreover, current legislation does not limit the development of voice-controlled systems
making it possible to multiply the uses and services afforded by the new information and
communication technologies, even more opportunities that can result in an increase in the
exposure to the risks of distraction while driving.
These observations have led the group of experts to direct their suggestions for action to the
regulatory aspects, on-board devices likely to accompany these regulatory measures, with
the deliberating processes for appropriating scientific knowledge by the stakeholders
involved making it possible to improve and adapt regulations.
SYSTEMATIZING THE COLLECTION OF INFORMATION BY LAW ENFORCEMENT OFFICIALS ON
MOBILE PHONE USE WHILE DRIVING DURING A ROAD ACCIDENT
The fact that information on mobile phone use while driving is currently not systematically
taken during an accident in France does not make it possible to precisely know the share of
accidents wherein the use of these technologies could be involved. So, it is difficult to
evaluate the stakes of this.
The pertinence and the evaluation of a specific regulation on mobile phone use while driving
requires that governments have data that is sufficiently precise on the involvement of this
use in the occurrence of an accident. However, existing research insists on the sporadic
nature of collecting this information. Law enforcement officials need to systematically
document mobile phone use as a possible cause for accidents. The Accident report and the
national file of road traffic accidents must consequently be adapted.
The group of experts recommends to systematize and to standardize the collection of
information on mobile phone use by the driver within the framework of accident reports
established by law enforcement intervention units. Better knowledge of the mobile phone
use and of other on-board technologies in the accident reports established by law
enforcement would represent fundamental data not only for evaluating the risk linked to
their use, but also to define road prevention actions.
Collective Expert Report
- 144 -
13/12/2011
SHORT-TERM DEPLOYMENT OF TECHNOLOGICAL
COMMUNICATIONS IN RELATION WITH REGULATIONS
SOLUTIONS
FOR
MANAGING
Scientific data shows that a mobile phone conversation led by a driver even with a "handsfree" mobile phone constitutes a cognitive distraction which disturbs his driving capacities.
Voice-controlled systems, for example, do not overcome this distraction. According to the
estimations, based on epidemiological data, the risk associated of an accident is multiplied
by 3 regardless of the system used. This risk is to be remitted along with the other risks of
accidents that are known and quantified in order to define regulations that are in coherency
with a road safety plan.
In order to accompany regulations on the conditions for mobile phone use in a vehicle,
technological solutions could be sought in order to induce "passive safety" (transfer of
incoming calls to voice mail, limited communication time, taking the road context into
account, etc.).
The group of experts recommends promoting the development and the distribution of
technological tools making it possible to facilitate the application of the regulations.
MAKING IT MANDATORY TO PROVIDE INFORMATION ON THE RISKS IN THE USER'S MANUALS
OF ON-BOARD DEVICES IN AUTOMOBILES
Current legislation indicates that "Placing within the field of vision of a driver of a vehicle in
motion of a device that is operating with a screen and which does not constitute assistance in
driving or in navigation is banned." (Article 412-6-2 of the Highway Code). However, we are
seeing a diversification in the possibilities for using mobile telephony in a road vehicle using
systems that are on-board or not and comprising a screen.
As such, the standardization and the development of technologies making it possible to limit
the use of mobile telephony systems during driving require a partnership with stakeholders
of which the technological and commercial choices can have an impact on this use, in
particular manufacturers of automobiles and operators and manufacturers of mobile
telephony.
The group of experts recommends that governments require manufacturers (of automobiles
and of mobile telephony devices) to distribute information on the conditions for the proper
use of the telephony devices and on-board systems in the car. Manufacturers must begin by
providing a reminder of current legislation.
SETTING UP A PROCESS FOR DELIBERATION BASED ON SCIENTIFIC DATA FOR A POSSIBLE
CHANGE IN THE EXISTING REGULATIONS
The very fast developments in communication and information technologies that can be used
in driving require regular adaptation, taking the knowledge acquired on the impact of these
technologies in terms of road safety into account.
Implementing a process for concertation and deliberation bringing together very diverse
stakeholders concerned with the stakes of road safety (public authorities, manufacturers,
operators, experts, insurers, employers, employees, etc.), would make it possible to share
information for the purposes of making a decision and better acceptability.
The group of experts recommends making a concerted effort aimed at improving the existing
regulations and in particular in adapting it better to the new uses of mobile telephony. This
Collective Expert Report
- 145 -
13/12/2011
reflection could be carried out within the framework of a deliberating process making it
possible to find a consensus on this subject within the stakeholders involved.
Actions for educating drivers and professionals
At least one driver out of three, even occasionally, uses their mobile mobile phone while
driving. It is men, young people and people that drive the most, in particular for professional
reasons, that have the highest rates of mobile phone usage while driving. Furthermore, these
frequent users are characterized by a lesser perception of the risk that is taken.
This data suggests that public actions that do not stem from sanctions and repression, but
which intervene on the representations of the risk and on the contexts of use (professional
situations), are to be reinforced, in particular through information campaigns and
educational efforts.
Three publics can be targeted: the general population of drivers, inexperienced drivers and
drivers using their vehicle for professional reasons.
CONTINUE SETTING UP COMMUNICATION CAMPAIGNS FOR DRIVERS ON A REGULAR BASIS
Although drivers are generally aware of the negative effects on driving of a visual-manual
distraction, they are not always aware of the cognitive distraction linked to mobile phone
conversation. Survey data shows the need to increase awareness of drivers to the risks taken
via a mobile phone conversation when they are driving even when they have a hands-free
system.
The communication efforts will make it possible to inform drivers on the increase in their
reaction time and consequently on making decisions when they mobile phone, on the
difficulties encountered in order to sample and process road information.
The group of experts recommends that the communication campaigns emphasize the fact
that capacities in terms of attention needed to mobile phone (including with a hands-free
system) alter the ability to drive by resulting in a difficulty in exploring the environment and
in detecting the changes in the road scene as well and increase in reaction time and in
making decisions.
INCORPORATING INFORMATION ON THE RISKS LINKED TO MOBILE PHONE USE AND OTHER
ON-BOARD DEVICES INTO DRIVER TRAINING
The young (18-24 year-olds) are the largest users of mobile telephony in daily life since more
than 70% of them use it every day or almost. During driver training, it is important to carry
out efforts aimed at increasing awareness to the dangers of the mobile phone for new
drivers. The information given to driving students must mention the fact that using "handsfree" systems does not prevent the phenomenon of cognitive distraction and as such
constitutes a factor of risk for an accident.
The group of experts recommends, within the framework of information on the main risks
linked to driver behavior, to incorporate a module on the risks linked to mobile phone use
and other information and communication technologies while driving in the training for new
drivers.
Collective Expert Report
- 146 -
13/12/2011
PROMOTING A ROAD SAFETY APPROACH IN COMPANIES
The mobile mobile phone is considered as a tool for work by those who travel within the
framework of their profession. It makes it possible to better organize one's travel, and to be
able to warn one's employer, customers, or other people is an incident were to disturb the
journey, and even "save" time during the work day by combining driving and other
workloads (planning, controls, negotiations, reports, etc.). However, its use while driving
constitutes a proven risk. This risk must be taken into account by management and labor
partners so that companies or professional branches develop policies that are adapted to the
use of the mobile phone in the vehicle and distribute the good practices in this field, which
may involve an overall approach to reorganize work.
As the road risk is the number one cause of mortality on the job (including home-work
commute accidents, which are assimilated as on-the-job accidents), management and labor
partners of the Commission on accidents in the workplace and occupational diseases of the
National fund for health insurance of employees (CNAMTS) on 5 November 2003 adopted a
code of good practices concerning the prevention of the road risk on assignment entitled
"Preventing the road risk at work". This code reminds of the dangers linked to mobile phone
use when travelling, recommending to ban its use behind the wheel and regardless of the
technical device used. In order to maintain the "company-employee" relationship, it is
recommended that companies set up a protocol making it possible to handle required mobile
phone communications without danger.
The priority action of the work inspection services scheduled in 2011 on the road risk could
be the opportunity to collect enough elements from the field and to reflect on introducing
specific regulations into the Highway Code.
The group of experts recommends valorizing private initiatives aimed at defining good
practices for mobile phone use during professional travel, whether stemming from insurers,
companies or professional branches and to provide a reminder of the legal risks linked to the
penal and civil liability of the employee as well as of the employer. This entails increasing the
awareness of the interest in a reasonable use of the mobile phone tool and of on-board
communications, systems during professional travel, listed in a protocol defined by the
company. As a stake in safety at work, this question must be incorporated into the regulatory
action plans developed by companies and stemming from the evaluation of professional
risks, but also into the Company travel plans when they exist.
Studies on the risks linked to mobile phone use and other communication
technologies
The vast majority of the epidemiological studies that have made it possible to identify the
existence of a risk associated with the use of mobile mobile phones when driving were
carried out in countries other than France with a different road context (vehicles,
infrastructures, etc.). These studies are now old and do not make it possible, on the one hand
to know the change in the uses, and on the other hand to evaluate the risks linked to other
information and communication technologies as well as the risks for users of the road other
than drivers.
Collective Expert Report
- 147 -
13/12/2011
EVALUATING THE CHANGES IN THE VARIOUS USES OF THE MOBILE PHONE AND OF OTHER ONBOARD DEVICES
Mobile telephony is sector where the distribution of innovations is very fast. New mobile
phone concepts with new services are coming out on the market. The appropriation and the
use while driving of these products may be different according to the characteristics of the
drivers. Better knowledge of the uses of the mobile phone and of their change over time will
make it possible to answer the basic questions which are: "why, when, where and how
drivers use their mobile phone while driving?" in order to evaluate driver exposure to the
distractions linked to these uses.
Moreover, studies concerning the combined use of the mobile phone with other on-board
systems are lacking. Indeed, the number of driving assistance systems is multiplying,
concerning speed limiters/cruise control whether or not they are adaptive, lane change
prevention devices, anti-collision systems, etc. We can also raise the question on the fact that
these systems, which facilitate the task of driving, can also encourage drivers to use their
mobile phone even more while driving.
In order to know the actual practices and their consequences better, there are two methods
for observing the prevalence of uses: observation via a survey taker at strategic points on the
road and surveys via a questionnaire carried out on random samples. The first method
provides an instant prevalence of the use of the hand-held mobile phone; the second makes it
possible to obtain a habitual prevalence and to specify the characteristics of the users and the
types of uses of the mobile phone.
The group of experts recommends monitoring the change in prevalence in France of mobile
mobile phone use and of other information and communication technologies, in driving
situations as well as the various methods of use (possible combined with driving assistance
systems) in terms of frequency, type of use (calling, responding, SMS, internet), situations of
use and call reasons.
EVALUATING THE STAKES OF AN ACCIDENT ASSOCIATED WITH MOBILE PHONE USE AND OF
INFORMATION AND COMMUNICATION TECHNOLOGIES IN FRANCE
Mobile phone use and information and communication technologies while driving is by
nature, and relative to the situation of driving, an intermittent activity. If possible disturbing
effect on driver is therefore also intermittent. The way of measuring this exposure
determines for a large part the type de research to be set up in order to obtain reliable
estimations of the risks associated with this practice.
As such, only accidentological information such as the share of responsibility of the driver
and the moment and the duration of the mobile phone calls placed while driving relative to
the time of the accident (obtained either from mobile telephony operators, or from the
drivers themselves) would allow for comparisons between "exposed period" and "control
periods" for the same driver or between "responsible" drivers and "control" drivers, and
therefore obtain estimations of risks.
The group of experts recommends carrying out studies making it possible to measure in
France the risk of an accident linked to mobile phone use and the other information and
communication technologies and to estimate the number of victims that can be attributed to
this risk.
Collective Expert Report
- 148 -
13/12/2011
ESTIMATING THE RISK LINKED TO MOBILE PHONE USE AND TO THE OTHER INFORMATION AND
COMMUNICATION TECHNOLOGIES BY PEDESTRIANS AND TWO-WHEEL VEHICLES
The nomadic nature of the mobile phone allows it to be used at any time throughout the day,
regardless of the context. Because of this, drivers of any type of vehicle, including two-wheel
vehicles (with or without an engine) are concerned by mobile phone use on the road, as well
as pedestrians, users who are not taken into account within the framework of this expertise.
Studies are lacking on the risks incurred by these populations when they use a mobile phone
during their travels.
The various study methodologies mentioned for car drivers can be used for these categories
of road users.
The group of experts recommends carrying out targeted studies on accidents involving
pedestrians, cyclists and two-wheeled vehicles on the public thoroughfare, in such a way as
to estimate the risk of an accident linked to mobile phone use and the other information and
communication technologies by these users of the road.
Impact of information and communication technologies on the driving
activity
Although the impact on driving of mobile phone use for conversing has been studied quite
well, the effects of the new uses however which are being developed (writing SMS messages,
internet consultations, etc.) are not known. Knowing that manipulating a mobile phone or a
keyboard to dial, answer/hang up, read or write SMS messages, etc. add to the cognitive
distraction a deviation of attention from the road scene (causing in fact a momentary
interruption in the processing of information coming from the road environment), we can
raise questions on the disturbances generated by the new mobile telephony services.
Certain theories on the attentional processes that come into play when driving a vehicle
suppose that the driver will adapt his behavior to the situation, for example by slowing
down when he mobile phones. There is currently not enough data to validate this
hypothesis.
Moreover, technological tools that would make it possible to handle mobile phone
communications according to the driving situation must be evaluated as to their impact on
the attentional capacities of the driver before they are placed on the market.
STUDYING DRIVING PERFORMANCE WITH THE NEW POSSIBLE USES OF THE MOBILE PHONE AND
OF THE OTHER INFORMATION AND COMMUNICATION TECHNOLOGIES
There is still little research on the impact of the various types of mobile phone use (sending
and receiving SMS messages, internet access, etc.) on driving performance. Also, little data is
available on the effects, the task of driving, of receiving visual or voice information provided
by a navigation system as well as on the simultaneous use of the mobile phone and of
different types of devices and driving assistance systems (GPS, speed limiter, etc.).
It is interesting to include how the task of driving takes place in an environment where the
information and communication technologies constitute multiple sources of distraction that
are likely to interact, and even be developed further.
Collective Expert Report
- 149 -
13/12/2011
The group of experts recommends evaluating, in experimental studies, the impact on driving
performance of the use of new applications in mobile telephony as well as the simultaneous
use of different systems.
UNDERSTANDING THE STRATEGIES OF DRIVER ADAPTATION BETTER ACCORDING TO THE
AWARENESS OF THE RISK
Current scientific literature does not make it possible to determine to what degree mobile
phone use is linked to behavioral adjustments in the task of driving, in such a way as to
reduce the risk or to not exhaust one's attentional resources (for example, reducing speed or
increasing inter-distances). It also does not make it possible to understand if there are
individual differences in the implementation of these possible behavioral adjustments,
linked for example to age, driving experience, sex or driver personality.
The scientific research on this subject remains limited and the few results obtained are
divergent in particular on the identification of adaptation behaviors making it possible to
compensate the negative effects of the mobile phone on driving. Efforts in research are
required, in particular through studies is actual situations, to validate or refute these
hypotheses.
The group of experts recommends carrying out studies on the adaptation strategies of
drivers in the situation of mobile phone conversation and to analyze the individual
differences in their implementation.
DEVELOPING TECHNOLOGICAL RESEARCH FOR COMMUNICATIONS MANAGEMENT
Any source of distraction is potentially harmful from a driving standpoint, in association
with the complexity of the situations experienced, the multitude of variables to be processed
and the consecutive solicitation of the individual's attentional resources. If we hypothesize
that mobile phone use has an impact on driving safety when it is combined with other
parameters, and in particular when an unexpected critical situation is encountered, it can be
interesting to test tools that would make it possible to limit calls or to warn the driver when
the road situation requires all of his attentional capacities or when his driving behavior is
suggesting a lack of attention.
The group of experts recommends carrying out studies for perfecting technologies which
could allow for: the filtering of incoming calls according to a diagnostic in real-time of the
driving context; warning the driver when approaching a critical situation; diagnostic on the
driver's attention deficits that could result in a prolonged withdrawal from driving.
Socioeconomic evaluation of various measures
Little work has been done on assessing the measures taken against mobile phone use while
driving. The rare research that exists was carried out in the Anglo-Saxon countries (United
States, Canada, Australia). However, there is a problem when transferring results from one
space to another, in light of the major role played by the socio-cultural contexts in terms of
driving. Moreover, much of this research is now old and as such refers to uses of the mobile
phone which have greatly changed since then, in terms of volume as well as in the type of
use. Economic evaluations and evaluations on the impact on behavior of the regulatory
Collective Expert Report
- 150 -
13/12/2011
measures of the mobile phone use while driving are therefore needed in France and more
widely in Europe.
EVALUATING THE IMPACT OF LEGISLATION AND OTHER ROAD SAFETY MEASURES ON MOBILE
PHONE USE WHILE DRIVING
With the lack of ad hoc studies on the impact of legislation on the behaviors of drivers, it is
difficult to design any reorientation of existing public action. But, in order to get a complete
picture of the measure of public action developed in this area, assessing the impact of the
current law is not enough. The current regulations need to be inserted into wider range of
actions that combines control-sanction, driver education and the existing equipment.
The group of experts recommends doing assessments of the existing regulatory systems a
posteriori, in particular of the impact of the regulation and of all of the accompanying
measures aimed at overcoming behaviors at risk (communication campaigns, application of
sanctions via law enforcement officials, education, etc.). Tools such as pluralistic evaluation
methods or participative assessments can be useful for this.
STUDYING THE FEASIBILITY AND SOCIAL ACCEPTABILITY OF MEASURES CONCERNING THE USE
OF INFORMATION AND COMMUNICATION TECHNOLOGIES WHILE DRIVING
Although it is desirable to assess the existing measures and those being considered with
regards to their impact on the behaviors of users, on accidentology or on the overall
economy, it is also suitable to assess the acceptability of these measures by those who are the
intermediate recipients of them (road police, for example) and final recipients (drivers and
public opinion at large). It is known that the effectiveness of a public policy and its
sustainability depend on the acceptance of those for whom it is intended as motivation for
those who are in charge of implementing it.
The group of experts recommends developing studies on the individual, social and
professional "feasibility" and "acceptability" of the regulatory measures under consideration,
technological solutions restricting calls in the car and professional charters.
Different study methodologies can then be used: in situ experiments (including social
technologies, for example through the analysis of the work conditions of professionals on the
road and of their need to communicate) or approaches of the "experimental economy" type.
STUDYING THE ECONOMIC ASPECTS OF THE VARIOUS MEASURES CONCERNING TELEPHONING
WHILE DRIVING
A few studies carried out at the end of the 1990's at the beginning of the 2000's (United
States) evaluated a cost-benefit ratio of mobile phone use and show at best that there is a
balance between the gains (in terms of the economic valorization of the accidents avoided)
and the losses (in terms of the economic valorization of the mobile phone calls that were not
made). However, a study carried out in Canada (Alberta) in 2009 suggests that under certain
conditions, a banning of telephoning while driving could be interesting from a
socioeconomic standpoint.
In all of this research, the uncertainties and the biases are many and the results must
therefore be taken with precaution. But, all state that the final result in fact depends on a
single parameter: the valorization of mobile phone calls.
Collective Expert Report
- 151 -
13/12/2011
The socioeconomic studies treated hand-held mobile phones, not hands-free kits. A
particular study on the value of calls made from a hands-free kit would constitute an
international reference. The underlying hypothesis is that the value of the calls made from a
more costly tool would then also be higher.
The group of experts recommends carrying out a socioeconomic assessment in France of the
regulations concerning mobile phone use while driving, which supposes carrying out an
assessment of the economic value of calls made while driving.
STUDYING THE FEASIBILITY AND THE INTEREST IN REGULATING MOBILE PHONE USE WHILE
DRIVING VIA DIFFERENT FINANCIAL INCENTIVE STRATEGIES
A common instrument for orienting travel practices is regulation through prices. Making an
itinerary or a method of transport more expensive leads to a change in one's choice of
method or itinerary. Inversely, reducing motorway tolls or air and rail rates at off-peak
periods encourages a portion of potential users to travel during less-restrictive time slots.
As such, an increase in the cost of mobile phone calls, if it is not marginal, should result in a
decline in mobile phone usage. But the changes in rates concerning cell mobile phones are on
the contrary going down.
Special rates for communications made or received from a vehicle in motion should result in
less mobile phone use while driving, and even usage that is limited to "strictly necessary"
calls. This also supposes that it would be technically possible to differentiate the calls made
and received by the driver from those of the passengers.
The group of experts recommends studying different strategies that encourage proper use
(regulation via prices, for example), in order to direct practices towards more safety. One
idea is to limit usage to "useful" calls, by increasing the price for calls made or received in a
vehicle in motion. Another path would be a charter between the insurer and the driver with
a financial incentive for good driving.
Collective Expert Report
- 152 -
13/12/2011
Communications
Collective Expert Report
- 153 -
13/12/2011
Collective Expert Report
- 154 -
13/12/2011
Distraction, telephoning while driving, driving routines
and cognition
The risk of distraction linked to mobile phone use in cars is obvious. This risk is known, and
gives rise to publications in all western States. In France, INRETS research mentions an
additional risk of an accident of a factor of 5 with a hand-held mobile phone, and a factor of 4
with a hands-free kit.
But the evidence does not equivocate to a response, or even hasty condemnation. Three
arguments can be developed: on content, on form and finally on a systemic level.
As to content, the cognitive risk linked to the mobile phone is poorly studied. Cognition has
an immense capacity to work in a sophisticated routine mode. Everyone knows, and science
proves it, that these sophisticated routines, having their own control mechanisms, are able to
successfully handle very complex situations over rather long periods of time: activation of a
lattice of routines using the initial plan, delegating control to affordances borne by the
environment, feedback to the attention call only at the end of guidance, with a result
obtained, or the case where the routine is blocked (refer to an analysis in Noizet and
Amalberti, 2000, for a review of the question).
The attentional channel (consciousness) is paradoxically released (even though this is a
limited resource), and is invested in other fields of interest. The problem therefore is not the
investment of consciousness in something other than the immediate demand concerning
driving; this in any case will be the normal case… as soon as cognition has programmed its
routines according to the context and considers that it is in a position to control the situation
(see Amalberti, 2001a and b).
The second paradox is that this free attentional channel is sporadically invested in the
present (perceptible information), but reserves a substantial part of its investment (80% and
more) for the past (explanation on past misunderstandings of the journey), the future
(anticipating the trajectory and navigation) and even more frequently on private objects that
have no link with driving. This is how cognition's main balancing works (see Hoc and
Amalberti, 2007 for a review of the question on this second paradox on the additional
compromises and cognitive adaptation).
Two results come out of this for mobile phone use while driving.
Driving routines are unable to function if the attention directed to the mobile phone diverts
visual perception and therefore prevents the routines from self-feeding and self-checking
with the environment. It is therefore logical that any manipulation of a delicate mobile object
and with uncertain ergonomics be strictly prohibited in cars.
Routine driving cannot be prevented; it is even a privilege for experts and is in no way
dangerous itself. Once the plan has been set by consciousness, the delegation is often rapid
and total for the lattice of routines activated: it is therefore normal that attention in 80 to 90%
of the time released, and that it is invested in something else (past, future, private)…
cognition by nature detests emptiness… an "empty" cognition here would quickly provoke
drowsiness (Brehmer's theory).
But once the routines are active, they can at any time recall the attention if they become
blocked, finished, or in a situation of not being able to continue without a reorientation order
or a new plan. In this case, the problem is the disconnecting of attention and of consciousness
Collective Expert Report
- 155 -
13/12/2011
which is directed to another subject, which itself has its own values of appeal, of
incompleteness, etc. The more the current task on which attention is concentrated has
emotional characteristics, and which is not completed, the more difficult it is to abandon…
however, this area of cognitive disconnection is very poorly studied. This has been analyzed
a little in aviation, particularly combat aviation, with an organization of work learned with
pilots which fractions time and avoids engagements that are too handicapping as they
cannot be disconnected. Why not imagine allowing hands-free conversations by limiting
them to 20 or 30 seconds in such a way as to prohibit conversations with a stronger
emotional content: basically "yes to get a message across", "no to begin a discussion" (Valot
and Amalberti, 1989). In order to conclude a vast ground of interdisciplinary research, which
unfortunately is very rarely investigated by cognitive psychology, with a discipline in
research that has encountered much institutional difficulty for 9 years.
As to the form, the methodology that was used to build the INRETS results, as also the
results obtained in other countries, is rather debatable. Wickens' multiple resource theory is
outdated and has been strongly criticized since… But even a more recent model would also
yield rather close results, observing a slowing down in responses, and reduced availability in
telephoning.
Finally, from a systemic standpoint, but this joins back with the discussion on the content,
what exactly is meant by the figures obtained on the risk which organize the entire debate
(factor 5, factor 4 of additional risk)? What is the reference situation (factor 1) and how many
drivers each day are at this low level of risk (not tired, not stressed, not telephoning, not
drinking, not worried, not postprandial, not with a work load, etc.)? What is the type of
recombination model between risks that is thought of? Simple additive? And what about a
mother who cannot mobile phone and who knows that her child is waiting at school with
professionals who have to leave? What about a position equivalent to absolute zero: what is
the realistic risk additive recombinant threshold? What is the actual additional risk of an
accident for a blood alcohol content at 0.5 g when it is known that simple fatigue is worth
0.8 g (Dawson and Reid, 1997)? Of course, we can discuss the additive model, but I am
pleading strongly for a high threshold model (with the limit being the unacceptable in all
cases and being intransigent as to this level), not for a low threshold model (a precautionary
principle, but of which the isolated occurrence cannot be justified scientifically, which stems
from speculation on the combination model, and for which a certain degree of interpretation
is left as to the sanction control). With this small set of low thresholds, we will especially hit
the residual "straws" which can be visualized and controlled even if they have no risk value
themselves (alcohol with very low thresholds less than 0.2 g/l, mobile phone), leaving the
"beams" uncontrolled (medications, contexts of anxiety, etc.).
To summarize my thoughts and my suggestions:
•
there is an additional risk when telephoning (as there is an equivalent or higher
additional risk in investing in other cognitive fields);
•
there is a very high additional risk in taking your eyes off the road: it is therefore
legitimate to fully ban standard mobile phones, perhaps by using technology in
the car that scrambles emissions-receptions;
•
it is no longer possible to suppress the mobile phone in the car, an accessory
among so many others in a communicating society of the 20th century,
surrounded by alerts, alarms, and diverse types of guides. We cannot prevent the
mind from investing elsewhere… the problem will be to remobilize it when
necessary.
Collective Expert Report
- 156 -
13/12/2011
Thought must be given in authorizing only original manufacture installations and that have
particular characteristics, with active scrambling, and perhaps an authorized duration that is
limited for each call in order to assist the cognitive disconnection and a repriorization of
attention (I am not for second-hand installations).
Finally, the precautionary positions for a use, with a narrow vision (silo model, with no
exchange between the risks) are without a doubt more dangerous than positions of
compromise between risks, combined with driver education that is really dispensed,
including by automobile manufacturers when they deliver their cars.
René Amalberti
Medical instructor, Doctor of psychology on cognitive processes
President of Group 2 of the Predit - Quality and Safety in transports
Care safety advisor for the Haute Autorité de Santé (French National Authority for Health)
BIBLIOGRAPHY
AMALBERTI R. La maîtrise des situations dynamiques. Psychologie Française 2001a, 46: 105-117
AMALBERTI R. The paradoxes of almost totally safe transportation systems. Safety Science 2001b, 37:
109-126
DAWSON D, REID K. Fatigue, alcohol and performance impairment. Nature 1997, 388: 235
HOC JM, AMALBERTI R. Cognitive control dynamics for reaching a satisficing performance in
complex dynamic situations. Journal of Cognitive Engineering and Decision Making 2007, 1: 22-55
NOIZET A, AMALBERTI R. Le contrôle cognitif des activités routinières des agents de terrain en
centrale nucléaire: Un double système de contrôle. Revue d’Intelligence Artificielle 2000, 1-2: 107-129
VALOT C, AMALBERTI R. Les redondances dans le traitement des données. Le travail humain 1989,
52: 155-174
Collective Expert Report
- 157 -
13/12/2011
Collective Expert Report
- 158 -
13/12/2011
Travel speed and other road accident factors
The goal of this presentation is not to modelize the risk of an accident (in terms of estimating
the parameters of the model), but to set forth, as simply as possible, the principle of the
relation between travel speed and risk of an accident on the one hand, between the other
factors for an accident and this speed on the other hand. Accident indifferently means a
damage or personal injury accident, whether or not fatal, and the risk of an accident is the
probability of the latter occurring, in a given context (of infrastructure, traffic, weather, etc.),
using as a reference a "basic" driver having no accident factor other than the speed of his
vehicle (the latter having given technical characteristics).
What can be said about the speed factor?
•
At zero speed, the risk of an accident is zero;
•
Above a certain speed (500 km/h? 1,000 km/h? regardless of this value here), an
accident is certain (a risk of 1);
•
Between these two extremes, the risk of an accident is a strictly increasing function
of the speed practiced.
How can this risk be modelized?
Primary risk of an accident
•
As the "reaction time" is considered to be constant regardless of the speed
practiced, the primary risk is a function of the speed (x) which contains a term of
order 1;
•
As the braking distances are proportional to the kinetic energy of the masses in
motion, the primary risk is a function of x which also contains a term of order 2;
•
As the risk of an accident is cancelled out for x=0, it can therefore be expressed:
Pr[Acc]=a1x2 + b1x
Secondary risk of death (or of an injury, whether or not serious)
As injuries are caused by phenomena either of abrupt deceleration, or intrusion, their risk is
therefore proportional to the kinetic energies (relative) of the various constituents of the
human body and those of the other masses in motion.
And if it is taken, as a first approximation, that these energies are proportional to the kinetic
energy of the masses in motion before the occurrence of the accidental circumstance, the
secondary risk of death (or of an injury, whether or not serious) is a function of the second
order in x.
Collective Expert Report
- 159 -
13/12/2011
As the risk of death (or of an injury, whether or not serious) is cancelled out for x=0, and the
taking into account of a term of order 1 not having a justification a priori (but nothing
prevents this from being considered), the following can be written:
Pr[Dcd / Acc]=a2x2
Global risk of a fatal accident (or of an injury, whether or not serious)
From fact, we know: Pr[Dcd]=Pr[Dcd / Acc] x Pr[Acc], giving the risk of having an accident
and dying in this accident:
Pr[Dcd]=a2x2 (a1x2 + b1x)
or
Pr[Dcd]=ax4 + bx3
Note that coefficients a and b are to date are those the least known (and are a function of a
multitude of parameters), but for which we can give average estimates that are acceptable for
speeds observed today (for example from 0 to 250 km/h), i.e. coherent with what we know
today from road accidentology and which would sufficiently reflect "the average driver" in
order to give credit to the demonstration of the principle covered by this presentation.
How can the other factors of an accident be taken into account?
It is commonly accepted that such and such an accident factor multiplies the risk by a certain
quantity (greater than 1 and that the epidemiologist calls the relative risk RR). And this,
"with all other things being equal".
In fact, in general, the question is not knowing whether this relative risk is a function of the
travel speed. In other terms, the absence of interaction (in the statistical sense of the term)
between said factor and the travel speed is assumed.
Under this hypothesis of non-interaction, the risk of death (or of an injury, whether or not
serious) attached to any factor whatsoever can be written:
Pr[Dcd]=RR (ax4 + bx3)
In practice, the inherent curve for this factor is deduced by a simple change of scale of the
curve reflecting the referral "basic" driver (figure 1).
Collective Expert Report
- 160 -
13/12/2011
Figure 1: Risk of an accident (fatal) according to the speed practiced according to whether or not the
driver is under the influence
Comments
The "zero risk at zero speed" postulate seems to throw out the case where a stopped vehicle
is involved in an accident. Such an accident however supposes that another driver is driving
at a non-zero speed. It therefore suffices to refer to this other driver in order to include this
type of accident in our reflection. Likewise, the postulate of a strictly increasing relationship
between speed and risk seems to exclude, for example, the case of a "slow" vehicle hit in the
rear by a "faster" vehicle (the slow vehicle would reduce its risk of being hit by moving
faster). But, here again, it suffices to refer to the faster driver in order to satisfy the postulate
of an increase in the risk with speed.
The proposed speed-risk relationships of an accident were presented as being inherent to a
given driver, at a given instant, in given circumstances. This is therefore only a possibility
among a multitude, therefore of no great interest a priori for assistance in decisions. But they
can also be considered as the reflection of the average of all of these "elementary"
relationships. Then, an analysis of them is certainly of interest in interpreting the "average"
road risk, and therefore for the public decision.
The fact that the risk of injury (possibly fatal) on roads can be a function of order 4 of the
travel speed is not commonly accepted. Some limit this by considering only the secondary
risk, of order 2 (cf. supra). Other assert that it would only be the fatal accident that would be
of order 4 (with a non-fatal injury accident only being of an order 2) 15 : this distinction can be
surprising in that it is perfectly established that it is possible to survive injuries that are
potentially fatal (in other terms, for the same injury, an accident can be fatal or not, without
this issue having any such link with the speed). And still others prefer to consider, and justly
so without a doubt, more sophisticated parameters, such as decelerations or relative speeds
at the time of the impact. But these parameters remain closely correlated to the travel speed.
15 LASSARRE S, HOYAU PA. Évolution récente du risque routier en France et en Grande-Bretagne. In: Les régimes français et
britannique de régulation du risque routier. The vitesse d’abord. DELORME R, LASSARRE S (eds). Inrets Ed, synthèse, n°57,
Bron, 2008: 27-39
Collective Expert Report
- 161 -
13/12/2011
This in no way calls into question the finality of our demonstration : considering the travel
speed, rather than more "biomechanical" parameters, allows for a common reasoning on a
parameter that is directly accessible to public decision. Notwithstanding, the fact that there
are exceptions to the relationship proposed (even that the latter is just an approximation of a
more complex reality and more "dispersed" around a certain "average" reality) does not call
into question this "average" reality that we are trying to bring out here.
It is moreover entirely possible to imagine that the speed - accident relationship be of an
order that is even higher or that it have curve discontinuities (inherent for example to
"thresholds" of the driver's attentional capacities). This however would not call into question
the reasoning proposed which is primarily based on the increasing nature of this
relationship.
Likewise, there is no obstacle in thinking that the hypothesis of non-interaction between
travel speed and such and such other accident factor is abusive (and that not identifying it is
the reflection of the difficulty in apprehending said speed in most of the studies which aim to
quantify the role of the various factors of accidents). However, unless one supposes that such
and such parameter would be a risk factor at certain speeds and a protective factor at others,
such interactive phenomena would not further call into question the reasoning proposed
which simply supposes that such or such factor increases the risk of an accident inherent to
such and such travel speed.
If such a relationship is accepted, this naturally implies a constant increase in the risk with
speed (the first derivative being an increasing function of order 3), and therefore
"mechanically" equivalent gains for any reduction in the speeds practiced.
As such, the more the speeds are "reduced", the more decrease will be needed to procure the
same gains (changing from 90 to 70 km/h would be less effective than changing from 110 to
90 km/h, for example).
However, if we refer to a Gaussian distribution for the speeds practiced, centered on a speed
close to the authorized speed (and therefore the number of drivers in violation of the speed
goes down as their speed moves away from the authorized speed), it may be more effective
on the overall to ticket the (very common) small degrees of excessive speed than the (very
rare) highly excessive speeds.
At a given speed, a driver with a factor of risk multiplies the risk of a fatal accident
occurring, for example, by the RR that corresponds to this factor. In other words, this same
driver would induce the same risk as the basic driver as long as he practiced speeds that are
as low as the associated RR is high.
However, regardless of the extent of this RR, this "equivalent speed" cannot be zero: banning
a driver from using the road with the excuse that he has such or such a risk factor is therefore
a fundamentally "conservative" measure.
From another standpoint, if we reduce the speeds practiced (for example, via automated
sanction control) for all drivers, we would reduce the risk attached to any driver, including
that for drivers having such and such a risk factor, and this by the same proportions. In
particular, if we take the driver who is under the influence, and admitting that the latter is as
"receptive" to automated sanction control as the basic driver, his risk should go down by the
same proportions as that of the other drivers. In other words, the fraction of the risk that can
be attributed to alcohol or cannabis should remain constant: the number of accidents that can
be imputed to cannabis or to alcohol should decrease by the same proportions as the total
number of accidents.
Collective Expert Report
- 162 -
13/12/2011
This affirmation also responds in part to the debate of knowing whether the recently
observed spectacular decreases should be attributed, entirely or in part, to automated
sanction control and to the reductions in speed that it induced. Not imputing a portion of
this to the reduction in speeds, but to other factors of which the imputability would have
decreased (such as driving under the influence) is legitimate in the common referral for
stakeholders in road safety (and in particular for decision-makers). However, except for a
simultaneous and spectacular change in the prevalence of these other factors in drivers in
circulation, this interpretation is fundamentally (in the primary sense of the term) in error:
reducing speeds "mechanically" reduces the impact of the other factors.
Furthermore, by shifting the distribution of speeds downwards, we reduce the proportion of
the most violent impacts and therefore the risk of death of those involved: the average
number of victims that died per accident should also have gone down. In other terms, the
number of people killed should have gone down more than the number of fatal accidents.
The same reasoning, and the same models, could be applied to the protective factors (such as
wearing a seatbelt). Such an approach would moreover not be new. In 1968, for example,
Bohlin "reconstituted" the circulating speeds of vehicles in order to identify the relationship
between travel speed and the risk of death according whether or not the driver had his
seatbelt on: his results are most conforming with what is asserted here 16 .
Put forth as such, the real foundation for road insafety is that no user of the road can travel at
a speed of zero! In fact, speed is not a factor for accidents as the others, because it is inherent
to the very notion of travel. Speed constitutes the only genuine causal factor of accidents, the
other factors that are normally mentioned as such are only secondary factors (if only in that
they are non-operational at a speed of zero) that "only" accentuate the speed-accident
relationship (or reduce it for protective factors).
Bernard Laumon
Director of research
Unit for epidemiological research and transport work environment monitoring (Ifsttar/UCBL)
French institute of sciences and technologies for transportation, planning and networks
16 BOHLIN NI. A statistical analysis of 28,000 accident cases with restraint value. Reprinted November 1968 from SAE
Transactions, vol. 76 by Society of Automotive Engineers, Inc. Two Pennsylvania Plaza, New York, NY 10001
Collective Expert Report
- 163 -
13/12/2011
Collective Expert Report
- 164 -
13/12/2011
Telephoning while driving: what are the biases17 ?
Extending the ban on mobile phone use while driving to devices the free up hands was
recommended by ONISR 18 and its committee of experts. The problem is not the occupation
of the hands, but the occupation of the mental capacity to be available for driving. The
knowledge acquired made it possible to assert with a risk of error largely below that which is
usually accepted to decide that:
•
telephoning while driving reduces attention;
•
the excess in risk produced is higher than with those observed with factors that
had been supervised by legislation justifying imprisonment (driving under the
influence of cannabis).
When considering "biases", I am including all factors of influence, for example, conflicts of
interest. When, after the presentation of the aforementioned expertise, the National Road
Safety Board (CNSR) votes a recommendation to extend the ban on use while driving to the
"hands-free" mobile phone and that its chairman immediately requests a second vote after
having developed arguments against this ban, we must examine the possibility of a conflict
of interest. Did the chairman of the CNSR have a link with the telephony industry, was this a
link of a nature that would influence his choice? Identifying a conflict of interest is not an
argument making it possible to assert that a stakeholder has acted against his convictions
and to refute the validity of his position. It can however lead to an absence of intervention
and of a vote in an assembly where the subject of this conflict is being debated. Furthermore,
visibility for this conflict of interest is important in order to inform the decision-makers, who
will make use of a decision taken with the active participation of a person in this situation.
This knowledge is particularly useful when a vote of which the result is against an industry
is immediately questioned by a chairman of the session who is in this situation.
Running an expertise on the data that is available in "pertinent and sincere" literature is one
thing. Being the involuntary accomplice in a desire to stall for time by requesting another
expertise is another thing. I am interpreting the order for another expertise on this subject as
a desire to delay the adopting of a measure which is needed in France, as it has been
imposed in countries where the rationality of the debate has prevailed.
As conflicts of interest in public management have to be controlled, the influence of conflicts
of attention must be reduced in handling an automobile, a motorcycle, a heavy truck or a
bicycle. The more we wait to reduce this factor of risk, the more it is going to be difficult to
do. It is not because an industry develops an instrument that renders services that it has to be
used everywhere and in any such fashion.
The "biases"
According to what I have read in the serious studies analyzing the approximate relative risk
of having an accident while telephoning while driving in relation to someone who is not
17
"Biases" being taken in the sense of poorly known potential factors of influence and which are suitable to be considered
18
Observatoire national interministériel de la sécurité routière (National interministerial observatory for road safety)
Collective Expert Report
- 165 -
13/12/2011
telephoning, distinguishing the "hands-free" risk from the "hand-held" risk, the biases that
were not studied currently seem to be of a reduced number.
I think the most important of these biases is the difference in the exposure to the risk and the
influence that it can have on the calculation of an odds ratio.
Many descriptive statistics and the analysis of them by researchers have identified the
importance of the reduction in the risk of an accident by kilometer travelled (and therefore
for the time of driving, even if the speed is a factor which plays a role) according to the
number of kilometers traveled in the year (figure 1).
Figure 1: Annual frequency of claims with following according to the average annual bracket of
kilometers traveled in 1980
The mathematical average of the kilometers travelled by the vehicles and, not the middle of the distance classes.
This notion is not new. The figure above comes from a document published in 1986 in the
collection of statistical data on automobile insurance in France from the AGSAA 19 . It is
constantly silenced or under-evaluated in multiple studies that express a risk of a road
accident. Hélène Fontaine has shown this in the case of accidents involving the elderly. Many
studies have calculated the risks of being killed according to age without taking into account
on the one hand the vulnerability (receiving a serious injury or dying "more easily" in an
impact of a given violence) and on the other hand of the annual distance travelled. A driver
who drives few kilometers each year has a risk of an accident per kilometer travelled that is
much higher than a driver who drives 50,000 kilometers a year. The incidence curve for
accidents is hardly modified above 30,000 kilometers a year.
In Suzanne Mac Evoy's article (2005) which is often mentioned rightly so, we do not see any
taking into account of this factor of risk that varies from one driver to another (compare
tables 1 and 2 of the article). A study prior to that of Mac Evoy took mobile phone billing
information into account but it is difficult to connect this with the practice of telephoning
while driving (Laberge-Nadeau et al., 2003).
It is important to note that the concordance is good between the evaluations of the relative
risk of telephoning while driving carried out with a "good method", in different contexts. The
Redelmeier and Tibshirani study (1997) had already produced results close to those of Mc
Evoy.
19 Association générale des sociétés d’assurance contre les accidents (General association of insurance companies against
accidents)
Collective Expert Report
- 166 -
13/12/2011
We have the experience of the difficulties in establishing an odds ratio in areas where the risk
is low and irregularly associated with other factors of risk. It is interesting to make the
comparison with the establishing of the cannabis risk. When Marie-Berthe Biecheler (2003)
had drafted a chapter on the risk of "cannabis and driving", the few studies available
produced results which did not make it possible to come to a conclusion, for reasons of size
as well as method. The SAM study (Narcotics and fatal accidents on roads) was needed to
reach solid ground, and again, with "small revisions" that came out during the refining of the
results with the taking into consideration of factors of influence. This study did indeed show
the importance of the precision in taking associated factors such as alcohol into account, but
also notions that are more difficult to quantify such as "fatigue" (travel that is sometimes long
to a disco, dancing a part of the night, more travel with fatigue, road often not known well,
presence of passengers who are all talking together, etc.).
This taking into account of the annual distance and of the frequency of use of a hands-free kit
(as factors for reducing the risk) is not in my opinion a reason to authorize this use in heavy
road users, substantial "mobile phone users", but to draw attention to the fact that the stricter
and stricter application on the ban on telephoning with hands occupied, without extending
this to a ban on hands-free kit, risks provoking a migration of casual drivers, small "mobile
phone users" to hands-free kits, without benefitting from the possible reduction in the risk
through intensive practice. We must therefore be attentive to the fact that the slightly lower
relative risk in the Mc Evoy study may be linked to different uses in different contexts. It
must therefore not be extended abusively to other users who would not have the profiles of
current users of "hands-free" mobile phones.
In conclusion, we have quality studies that establish a high relative risk of being involved in
an accident when telephoning, regardless of the type of mobile phone used. These studies
are sufficient to say that all forms of telephony while driving should be prohibited, unless
returning to a ban on the hand-held mobile phone in order to retain coherent regulations.
It is possible that the differences observed between the levels of risk depend on the
characteristics of the driver which are currently not taken into account (annual distance,
crossed with the hands-free/hand-held distinction).
We do not have much at all in terms of treatment through regulations of the attention
disturbances that can be avoided.
Of the three major factors of risk: non-adapted or illegal speed, excessive blood alcohol
content, "alteration of the psychological and cognitive state of the driver", we can easily
control the first (automatic radars of which new forms can be developed), rather difficultly
the second (the user has to be intercepted and made to blow into a breath test) and very
difficultly the third. There are processes which make it possible to de detect the beginnings
of falling asleep (movements of the eyes, eyelids), but we are far from an organized
implementation on the fleet of automobiles. As for attention disorders, this is even worse
than for vigilance, we cannot monitor the reduction in attention in real time, we can only
prevent it from becoming degraded by banning practices identified as reducing attention.
With regards to this request for expertise (necessary?) to Inserm and INRETS, the difference
must be made between expertise of knowledge, expertise for decisional purposes and
militant action.
It is legitimate for an expert to separate the following:
•
what the scientific community has produced in the area of knowledge on the
subject;
Collective Expert Report
- 167 -
13/12/2011
•
what I know of the various choices possible faced with the problems that you are
facing and which have been identified by the expertise on knowledge;
•
what I recommend to you if your objectives are the following (and then I list the
objectives that can be considered) and here is why (advantage/disadvantage
analysis).
It is then possible for an expert to be on a different plane, that of "activism" and to say, in
light of what we know, what we could do, and references which are yours, not taking such a
decision engages your responsibility. He then acts as a citizen, possibly downstream of the
recommendations that he was able to give. I had this attitude several times (like some
scientists that had participated in the collective Inserm expertise on asbestos) and this does
not pose any problem for me, everyone is in their legitimacy when answering a request for
knowledge or a request for a decisional opinion within the framework of the assignment that
he is entrusted with, each citizen is legitimate when he writes that the absence of decisions in
a defined field has consequences that are unacceptable in his opinion, when socially and
technically acceptable measures of prevention were possible.
Experts who say: here is what we know about the use of devices such as the various forms of
telephony, SMS, guidance used when driving a vehicle and about their risks.
Experts who draw decisional consequences of the type: the legitimate political power having
made the choice to ban the hand-held mobile phone while driving, it would be coherent to
extend the ban to the hands-free mobile phone, in light of what we know on the risks linked
to this practice. We recommend this decision. It is then indispensable to take an inventory
not only of the objective risk, but of the entire problem in a social context, and even economic
context by taking an inventory of the decisions taken in other countries, in particular in the
United States who are reacting greatly to this problem, with the advantages and the
disadvantages of the choices retained.
Claude Got 20
Honorary instructor at the Faculty of Medicine of Paris-Ouest, Université René Descartes
Expert on Impact biomechanics and accidentology
BIBLIOGRAPHY
BIECHELER MB. Cannabis, conduite et sécurité routière: une analyse de la littérature scientifique.
Note de synthèse de l’Observatoire interministériel de sécurité routière, February 2003
LABERGE-NADEAU C, MAAG U, BELLAVANCE F, LAPIERRE SD, DESJARDINS D, et coll.
Wireless mobile phones and the risk of road crashes. Accid Anal Prev 2003, 35: 649-660
MCEVOY SP, STEVENSON MR, MCCARTT AT, WOODWARD M, HAWORTH C, et coll. Role of
mobile phones in motor vehicle crashes resulting in hospital attendance: a case-crossover study. BMJ
2005, 331: 428
REDELMEIER DA, TIBSHIRANI RJ. Association between cellular-mobile phone calls and motor
vehicle collisions. N Engl J Med 1997, 336: 453-458
20
The author's standpoints can be found on the website: www.securite-routiere.org
Collective Expert Report
- 168 -
13/12/2011
Prevention of the road risk in the workplace: what can be
proposed?
The Steering committee for the prevention of professional road risk was defined by an interministerial order. It combines the Department of safety and road traffic (DSCR), the General
department of labor and the various plans, insurers of professional risks such as CNAMTS
for the general plan. It is particularly in charge of developing and suggesting pluri-annual
action programs that can be implemented by the various plans.
Professional road risk concerns all companies and all professionals who are on the road,
whether or not it is their profession. The difficulty for insurers of professional risk comes
from what the company is used to providing concerning its professional risk it its workshops
or in its factories, but not on the public space which is the road. For the company, an
employee traveling on the road is a person on which it has little influence and the company
is often poorly armed and informed about this type of risk.
However, The Labor Code clearly specifies the need for an employer to define the task to be
carried out and this, in optimum conditions of safety, since he must preserve the health of
the people at work, thus setting an objective of safety results. On the other hand, social
security is concerned for the general plan as an insurer of bodily injury occurring in
employees. Home-work commutes and those during an assignment are then those that are
covered.
A substantial proportion of companies have yet to incorporate this risk. When confronted
with this in the field, you can realize that few companies have taken this on. A survey of the
French National Sickness Insurance Fund showed, for light duty vehicles in particular, that
one company out of two, using this type of vehicle on a daily basis, has not incorporated the
road risk into its single risk evaluation document, which is however specified by the Labor
Code (figure 1).
Figure 1: Various stakeholders involved in the professional road risk
The activity of driving within the framework of work is ambiguous as it unfolds in a public
area (the employer is there alone, the connection of being answerable to the company is
there, but it is weaker than in the company) and is ambiguous as to the status of the vehicle
(often, the employee's personal vehicle is used for professional purposes). The
responsibilities are therefore not necessarily well established, in any case by the company.
Collective Expert Report
- 169 -
13/12/2011
Road risk is transversal and often poorly apprehended. In Alsace and Moselle, the feedback
from BAAC (analysis bulletin of personal injury accidents) sheets has shown that in 40 to
44% of the cases (for 80% of the BAAC sheets completed), according to the départements, there
is in a road accident involving bodily injury at least one person involved who was in a work
situation or on the commute. A major portion of the traffic on the roads is as such comprised
of professional travel.
The legitimacy is shared and is often difficult to discern. Professionals on the road are
concerned with the Highway Code, the Labor Code (obligation of prevention), the Social
Security Code for professional risk insurance, with the objective being to preserve the health
of the employee. Accidents aside, the road also has more insidious and long-term effects,
causing employees to suffer from occupational diseases in the case of professions with high
exposure to the road.
A professional road accident is a road accident and a vehicle accident as well as an accident
in the workplace. As a road accident, the State, governments, insurers have to get involved.
As a vehicle accident, this entails the insurers, and as an accident in the workplace, it
involves Social Security, Labor inspection, etc.
An accident on assignment is an accident that occurs with an employee on the road, under
the authority of the head of the company and during his work time. It is therefore an
accident in the workplace and the obligation of prevention is of the same nature as for all of
the professional risks.
An accident during the commute is also considered as an accident in the workplace, this is an
accident taking place during the commute driven by the insured party from his domicile to
his place of work and back.
This different context requires two different approaches in order to better prevent the risk on
assignment and for the commute risk incurred by the employee: for assignments, the
company can impose certain things, for the commute, this involves concertation with the
employee.
On the other hand, concerning the professional road risk, in the company, the frequency of
personal injury accidents is relatively low (10% of personal injury accidents in the
workplace). When a company of ten employees is surveyed (the average for French
companies is less than ten employees), they say they have few road accidents. It is "statistics
speaking" here. However, when an accident does occur, it is of a very serious nature: more
than 45% of fatal accidents in the workplace occur on the road (2008 figures).
For the company, this is therefore a risk that is often misunderstood, or poorly understood,
yet it is a risk characterized by its seriousness. Road accidents in the workplace form a
substantial share in fatal professional accidents.
Convergence of public policies
The Steering committee for the prevention of professional road risk follows a charter signed
by Road safety and the French National Sickness Insurance Fund in December 1999, in order
to converge two public policies: one which is to preserve the health of people in the
workplace and the other of which the purpose is to reduce road insafety. The steering
committee was created in 2001, bringing together the DSCR, the Ministry of Labor, and
CNAMTS. In 2006, it was enlarged to other social coverage plans for professional accidents
and accidents in the workplace: The famers' mutual (MSA), the National retirement fund for
agents of local authorities (CNRACL) for the public hospital function and the public
Collective Expert Report
- 170 -
13/12/2011
territorial function and, since 2007, the independent worker social plan (RSI). Today, nearly
23 million people at work are covered by the proposals of this steering committee or the
actions stemming from it, led by the members and partners of this committee (figure 2).
Figure 2: Composition of the steering committee for the prevention of professional road risk
Preventing professional road risk requires a strong commitment from the company. The
steering committee suggests active prevention actions, which go beyond those of the
regulations, with adapted and realistic objectives and strong acts of management.
The Commission on accidents in the workplace and occupational diseases (CAT/MP) of the
CNAMTS, defining the prevention policy of the professional risk sickness insurance branch
has adopted two texts. One, adopted on 5 November 2003, concerns the commitment of
management and labor partners on the prevention of the "assignment" risk and the other,
adopted on 28 January 2004, pertains to the commitment of management and labor partners
on preventing the "commute" risk. These texts are the basics for the commitment needed to
best prevent the road risk.
Good driving practices for the "assignment" risk
The first element concerns evaluating the road risk. As with any professional risk, this risk
has to be assessed and be subject to prevention, with an obligation for results. Indeed, the
employer is bound by the Labor Code to take an inventory and assess the risks that his
employees are exposed to "due to or during their work", risks which will be listed in the
"single document" for the company (order no. 2001-1016 of 5 November 2001), and be subject
to an effective action plan.
This entails acting in such a way as to limit the risks:
•
for example, by avoiding or limiting travel and by making use of alternative
means: travelling is not in fact always the best method to be effective and priority
must be given to the safest way to travel (train, plane, public transportation, etc.);
•
by setting up practical modules, for example to learn how to make the common
checks required for the proper operation of the professional vehicle, in order to
understand the risks linked to maneuvers (size, blind spots, etc.), to know how to
detect the danger zones and analyze driver behavior, in order to understand the
influence of speed on braking and stopping distances, on vehicle adherence, and
discover the loss of control, be aware of the risks linked to not wearing a seatbelt,
etc.;
Collective Expert Report
- 171 -
13/12/2011
•
by having a vehicle that is adapted to the travel and by making sure that it is set
up and equipped in order to allow for safe travel that is adapted to the activity of
the employee and by maintaining it is good working order. Propositions are made
concerning light duty vehicles in the twelve propositions in the white book "For a
safer utility vehicle";
•
by giving thought to the travel itself: reasonable itineraries, by preparing the
itinerary (the safest roads, roadwork, weather, etc.) and by taking professional
imperatives into account in order to travel safely (break time, etc.);
•
by setting up controlled communication: management and labor partners have
agreed to issue an opinion on the use of mobile mobile phones: "no mobile phone
communication while driving, regardless of the technical device", and by defining
the rules for managing the mobile mobile phone;
•
finally, a last thought on good practices relates to the required skills. For example,
in order to drive a light vehicle up to 3.5 tons, a "B" class permit acquired once and
for all is sufficient, without having to learn how to drive a vehicle of which the
load can vary over the course of the same day, how to assess the payload, fasten it
down, etc.
In sum, four axes for action have been determined: travel management, vehicle management,
communications management and finally skills management.
The texts have been acknowledged by the general social security plan, and adopted in
totality by the members of the steering committee for the assignment accident risks.
For the risks of commute accidents, the legal context is different: the line of subordination is
not established, there is no legal obligation of prevention, in the strict sense of the term; the
professional activity is one of the determinants of the risk; prevention of the risk is within the
scope of concertation (by encouraging carpooling or by setting up group transport, etc.). A
text of 28 January 2004 was adopted by the CAT/MP with regards to this. Prevention of this
risk must take its inspiration from the general principles of prevention and be the result of a
local agreement between management and labor partners.
Good driving practices for the "commute" risk
In terms of stakeholders, for the commute risk, there is the Highway Code, the insurer of the
professional risk, the insurer of the personal vehicle of the employee, etc.
Moreover, today, with the Solidarity and urban renewal law (SRU), les Urban travel plans
(PDU) and Company travels plans (PDE), an environmental issue and a sustainable
development issue come to the forefront in urban areas and it has an impact on employees'
commute travel (figure 3).
The issues linked to the health and safety of salaried workers need to be incorporated into
these developments linked to the PDU. Switching to "soft modes" such as two-wheeled
vehicles is perhaps a plus for the environment, but this can also generate accidents as has
been seen in some built-up areas.
There are indeed actions to be carried out, in a global way, and we again see that company is
a little depraved.
These good practices are recognized by the State and by all of the insurers of professional
risks. They form the base of the Steering Committee's 2006-2009 action program for the
prevention of the professional road risk.
Collective Expert Report
- 172 -
13/12/2011
The keys to an effective and sustainable action can be the setting up of a collective action
plan in companies that have the same local context (industrial zone, job pool, etc.) and
concertation with the local stakeholders in Road safety (territorial units, DDE, etc.).
Figure 3: Integrating the problems of the road risk into the Urban travel plans
Actions to be carried out or paths to more thorough research
These concern various fields that pertain to the road risk and in particular:
•
going deeper into the question of mobility in the workplace: mobility in the
workplace seems to be increasing and the issue with some professions is that the
vehicle sometimes becomes a mobile office, a mobile workshop… This leads to an
ever-increasing number of tasks to be carried out by the traveling employee. The
features and the technology of on-board equipment is changing very quickly and
this entails developing solutions to facilitate communication in complete safety;
•
on the questions of attention and mental load: what is the incidence of the
eruption of new technologies in the vehicle, driving assistance equipment,
equipment linked to the professional activity (means of communication, etc.)?
•
what typology of professions is concerned, what changes can be foreseen?
•
one field of investigation that is also to be addressed is the problem of health in the
workplace, with questions on life hygiene, incompatibility with driving
(alcoholism, medications, etc.), de physiological and psychological constraints, etc.
•
questions pertaining to skill: what skills are needed to drive for one's work? What
skills are required to use one's vehicle within the framework of work? Can we
speak of an authorization to drive? What about medical aptitude? What is the role
of occupational medicine? What exams are necessary (vision, hearing, medical
treatments, addictions, etc.)?
To conclude, we can say that reasonable mobility is the convergence of the issues concerning
road safety, safety and health in the workplace, the environment and sustainable
development, public health and health in the workplace.
Collective Expert Report
- 173 -
13/12/2011
Managing communications
Mobile mobile phones, just as certain on-board communication systems in vehicles, are
widely considered as a work tool for people who travel within the framework of their
profession. Making communications possible with the employer, customers, worksites, or
with those around you, it allows you to inform others and modify the unfolding of the
assignment in the case of an unplanned event. This seems, "a priori", to be a stress reducer
for the person who is traveling. However, ever-increasing recourse to the mobile phone
within a professional framework, with the objective of optimizing travel, can on the contrary
generate increased solicitation of certain employees who are traveling (after-sales service,
maintenance, construction site manager in the construction industry, etc.), with a risk of
substantially increasing the mental load of the employee during his driving activity.
The new technologies, including the cell phone, have an effect that greatly extends the
conventional limits of the workspace. Although the capacity to communicate and exchange
information, while traveling, provides the feeling of making it more effective and more
productive, it also greatly increases the causes of distraction for the worker who is driving
and the risks of an accident.
That is why the use of these on-board communication systems must be subject to rules that
are well defined and accepted in the company and by its partners (customers, suppliers, etc.).
As road risk moreover constitutes the top cause of mortality at work (including home-work
commute accidents, which are assimilated as on-the-job accidents), management and labor
partners of the Commission on accidents in the workplace and occupational diseases of the
French National Sickness Insurance Fund for salaried workers (CNAMTS) unanimously
adopted on 5 November 2003, a code of good practices pertaining to the prevention of the
road risk on assignment titled "Prevention of the road risk in the workplace". This
recommendation, later recognized by all the social insurers forming the Steering Committee
for the prevention of the professional road risk, recalls the dangers linked to mobile phone
use while traveling, recommending to prohibit its use while driving a vehicle and this,
regardless of the technical device used. In order to maintain the "company-employee"
relationship, it is recommended that companies set up a protocol that makes it possible to
handle the necessary mobile phone communications without danger.
In order to illustrate these recommendations and encourage their implementation, the
CNAMTS and Road Safety regularly sign "Road Safety" charters with companies or
volunteer professional branches so that the latter can develop adapted policies for mobile
phone use during travel and distribute the good practices in this area, which often involves a
global approach in reorganizing the work. This always entails calling into question the
principle according to which remote workers must be able to be contacted everywhere and at
any time by their employer and by their customers.
A few examples of professional situations
In an agro-foods company a fatal accident occurred involving a salesman who was driving
during a mobile phone communication with his company and which also caused the death
of a family following the collision. The company, in order to develop a communications
protocol, took a survey with volunteer employees, from among the categories of personnel
likely to travel, in order to know the information communicated during the assignments and
home in on the circumstances of the travel during which this communication is imperative.
Collective Expert Report
- 174 -
13/12/2011
After this survey, it was able to reorganize its departments in order to accentuate the role of
the stationary sales departments with regards to the clientele, as such reducing the flow of
data between itinerant sales personnel and clients and the related risks.
In a maintenance/industrial equipment repair company, the use of on-board positiondetermining systems are also based on a mobile phone link with the employee in order to
modify his schedule and have him intervene in the event of an emergency at request of a
customer who has a breakdown. What can be said about the mental load of the employee
that is diverted from his scheduled day in order to intervene in an emergency for a customer
who can no longer produce? This is the consequence of the act of communication while
driving: the employee will direct all of his attention, while driving to the location of his
future intervention, to preparing the act of repair (diagnostic to be carried out, spare parts
available, machine blueprints to be consulted, etc.) and to the content of his intervention
which generates a new situation of risk.
Without forgetting the mobile phone calls placed or received that will allow the employee to
better prepare and to reduce his intervention time (diagnostic by mobile phone with the
customer, discussion with the company's technical department, emergency control of spare
parts, etc.), an organization that is supposed to optimize and reduce stress can as such
largely increase the mental load. The secondary effects of this type of organization are
largely based on on-board systems (mobile phone and digital communication systems) and
can also, according to certain companies, generate an isolation of the employee, excluding
him from the company's social collectivity (psychosocial risks, etc.).
Another example: a company requests that its sales personnel agree to not mobile phone in
the car. As long as they have not signed the document, they cannot access the "professional"
computer application on their laptop computer, which is indispensable for them to be able to
report on their activity to upline management. So, of course, they sign but, in practice, they
continue to mobile phone while driving because it is the very way the company is organized
that requires this. During a sales meeting, we hear for example: "Ok, you can go now, you're
going to be late getting to the customer, and you've got two hours of driving ahead of you.
I'll call you one hour from now in order to give you the elements...". Or even taking orders
and the latest "live negotiations" during mobile phone calls made by the customer directly to
the salesperson for the last discount or a reduction in the delay, requiring the salesperson to
"evaluate and decide" while driving.
One testimonial: "Banning the mobile phone does not mean banning the reception of a signal
and then stopping as soon as possible in order to communicate... This seems to me like a
good measure! Recently, I accompanied a patient to the hospital, and from the beginning
until the end of the trip the ambulance driver constantly received mobile phone calls, and
with a hand-held mobile phone! I admit that this was quite emotional, in that in addition he
was late and was driving very fast, is this normal? That said, he was just an employee;
perhaps certain employers need to be made more aware? Because who loses points, and
possibly their license, who is responsible in the event of an accident?… The pressure can
sometimes be a bit too high".
Instituting a communications protocol
It is therefore necessary to institute a communications protocol that allows employees on
assignment to remain in contact with their company and their customers, without
endangering their safety on the road.
Collective Expert Report
- 175 -
13/12/2011
This protocol must meet the needs of the company while still granting priority to the safety
of the employee. This is a document that the employee knows, which specifies under what
conditions the latter should use his cell phone when he is on assignment.
The communications protocol allows the employee to remain in contact with his company or
his customers without taking risks on the road. The following can be suggested for example:
•
reminding of the risks of accidents linked to cell mobile phone use while driving;
•
banning cell phone use while driving (by indicating this measure in the driver's
manual);
•
authorizing communication only when the vehicle is not moving;
•
recording a welcome message via voice mail;
•
automatic transfer of calls;
•
setting time slots for calling during breaks from driving;
•
organizing the centralization and management of mobile phone calls in such a
way that this instruction can be effectively applied by the employees.
Concerning the responsibilities, in light of the existence of this text adopted by the
management and labor partners, in the event of an accident of an employee on assignment, it
is the head of the company who could be responsible if no communications protocol has
been adopted.
As such, an accident in the workplace that has occurred due to a professional call on the
employee's mobile phone while driving will have all of the characteristics of an inexcusable
fault.
Examples of professional commitments
A testimonial from the management of an industrial cleaning company says: "It is clear; we
have banned cell phones while driving. I myself barely avoided a serious accident when I
was making a mobile phone call. I came very close… When they are driving, our employees
are under strict order to divert the line to their voice mail and to stop to process their calls.
We take this stopping time into account in the organization of rounds… this makes us lose a
little time, of course, but we gain in safety. And then, if something were to happen to one of
my employees while driving, I am first in line".
In May 2003, a road infrastructure manufacturer published posters and small leaflets
illustrating the dangerousness of using cell mobile phones while driving. In the form of a
comic strip called "An accident is just a phone call away", this campaign describes how an
accident was avoided in the nick of time at a crossroads. One of the two drivers in the
scenario was answering a call on his cell phone, which distracted him. The other driver,
more attentive, succeeded in avoiding the collision and drove to a parking lot to call back the
caller who was trying to reach him at the time of the incident. This story is part of a one-page
comic strip series, each illustrating a road risk, which is widely posted in the construction
camps of this company's work sites which has 20,000 vehicles in circulation 21 .
In conclusion, it is important to clearly remind the commitments taken by management and
labor partners of the Commission on accidents in the workplace and occupational diseases of
Source: Le risque routier en mission. Guide d’évaluation des risques. Institut national de recherche et de sécurité (INRS), ED
986, Septembre 2006
21
Collective Expert Report
- 176 -
13/12/2011
the CNAMTS on 5 November 2003 as well as the legal risks linked to the civil and penal
liability of the employee but especially of the employer. The latter can make use of a wide
communications campaign also making it possible to valorize private initiatives, whether
stemming from insurers, companies or professional branches.
This entails increasing awareness of the interest in a reasonable use of the mobile phone tool
and of on-board communications systems, during professional travel, listed in a protocol
defined by the company.
Forming a stake for safety in the workplace, this question must be incorporated into the
regulatory action plans developed by the companies and stemming from an assessment of
the professional risks, but also in the "Company travel plans (PDE)" when the latter exist.
The priority action for labor inspection services scheduled in 2011 on the road risk could
integrate a "communications" section in order to collect a sufficient amount of information in
the field so as to reflect on introducing specific regulations into the Labor Code.
Thierry Fassenot
Advising engineer to the Department of professional risks
Secretary of the Steering Committee for the prevention of professional road risk 22
CNAMTS (French National Sickness Insurance Fund for salaried workers)
22
Committee website: www.risqueroutierprofessionnel.fr
Collective Expert Report
- 177 -
13/12/2011
Collective Expert Report
- 178 -
13/12/2011
Safety implications of mobile phone usage by drivers:
Legal Situation, Research Studies and Outlook
The legal situation in the UK concerning mobile phone use, both hand-held and hands-free,
is described. Actual usage of mobile phones in vehicles while driving is reported based on an
observational study in London. Three specific investigations of mobile phone use in a
simulator are reported; these concern benchmarking impairment to alcohol, comparing
phone conversations with passenger conversations and investigating the effects of texting on
vehicle control. Some brief conclusions are drawn and possibilities for improving safety
concerning mobile phones and distraction are discussed.
Legal Situation in the UK
Highway Code
The Highway Code summarises recommendations and the law concerning driving. In terms
of law, proper vehicle control is required at all time and there is a specific offence of using a
hand-held mobile while driving. The law is denoted by “MUST” or “MUST NOT”
statements within the code. In addition, there are recommendations which are also taken into
account in a court of law (table I).
Table I : Highway Code Paragraph on Mobile Phones
Mobile phones and in-car technology
127: You MUST exercise proper control of your vehicle at all times. You MUST NOT use a hand-held mobile
phone, or similar device, when driving or when supervising a learner driver, except to call 999 or 112 in a
genuine emergency when it is unsafe or impractical to stop. Never use a hand-held microphone when driving.
Using hands free equipment is also likely to distract your attention from the road. It is far safer not to use any
mobile phone while you are driving - find a safe place to stop first.
Laws RTA 1988 sects 2 & 3 & CUR regs 104 & 110
Penalties for hand-held mobile phone use
There is a fixed penalty fine of £60 (rising to up to £1000 should the case be taken to court)
for using a hand-held mobile phone. Also, since February 2007, using a hand-held mobile
phone became an “endorseable offence”, attracting 3 penalty points. Making the offence
endorseable very much strengthened the penalty as attracting 12 or more penalty points
within 3 years means disqualification. The UK has a complex system of endorsements for
various offences and number of years before penalty points can be disregarded.
Health and Safety Law
Health and safety law applies to on-the-road work activities in the same way as it applies to
all work activities. Therefore the risks are to be managed effectively by companies within a
health and safety system.
The Health and Safety Offences Act 2008 raised the maximum fine which may be imposed in
the lower courts from £5,000 to £20,000 for most health and safety offences and made
Collective Expert Report
- 179 -
13/12/2011
imprisonment an option for more health and safety offences in both the lower and higher
courts.
The Corporate Manslaughter and Corporate Homicide Act, 2007 provides the ability to
prosecute companies and organisations for a gross breach of duty of care.
Police may check phone records when investigating fatal and serious crashes to determine if
use of the phone contributed to the crash. Employers who require staff to use any mobile
phone while driving for work could be prosecuted if an investigation determined that such
use of the phone contributed to a crash. Evidence of encouragement of drivers to use mobile
phones could lead to possible corporate manslaughter charges against directors of
companies (not the employees).
This health and safety legislation is widely understood by larger companies and advice on
implementation is provided by industry groups (e.g. Figure 1). However, for smaller
companies and self-employed people, the implications are probably less well appreciated or
may be ignored in favour of the perceived economic benefits of being potentially contactable
and available on the phone.
Figure 1: The BVRLA guide
Actual Use of Mobile Phones
Actual use of mobile phones (hand-held and hands-free) in the UK can be gauged from an
observation survey of 33 sites in London which is performed annually (Narine et al., 2010).
Although there are, undoubtedly methodological challenges with such an observation study,
the annual repetition provides, at least, a relative measure and a broad indication of use. The
most recent results are presented in Figure 2 and Figure 3. In particular, there is a statistically
significant difference between 2008 and 2009.
Collective Expert Report
- 180 -
13/12/2011
Figure 2: Hands-free mobile usage in London
Figure 3: Hand-held mobile usage in London
Selected Recent Research
Redelmeier and Tibshirani work
This seminal paper (Redelmeier and Tibshirani, 1997) essentially concluded the debate as to
whether or not talking on a mobile phone whilst driving was a dangerous distraction. This
involved 699 Toronto drivers who had mobile phones and were involved in collisions
resulting in property damage but not personal injury. Calls on the day of accident and a
week before were analysed through billing records. Essentially, real world, simulator and
meta-analyses produce the same conclusions:
The risk of accident was four times higher when a mobile phone was being used whilst
driving (and raised for up to ten minutes after termination of the call). This suggests that the
impairment caused by the conversation remains after the driver has completed their call
because they remain preoccupied by the content of the conversation. This combined with the
result that there was no difference in the risk level for hand-held and hands-free calls gives a
Collective Expert Report
- 181 -
13/12/2011
strong illustration that it is the distraction caused by conversing with another person and not
the physical act of making a call that causes the driving impairment. The authors also state in
the report that driving whilst using a car-phone is similar to driving with blood alcohol level
at the legal limit.
The “4 times higher” risk has been quoted by UK Department for Transport in safety
information literature and has become one of the most well known statistics in the UK in this
field.
TRL Study on Mobile Phones and Alcohol
This study was carried out by TRL for the Direct Line insurance company (Burns et al., 2002).
There were 20 participants who drove in TRL’s high fidelity driving simulator to undertake
a car following exercise in traffic, in curves and in an urban setting. Alcohol was
administered to reach the UK legal limit -80mg/100ml blood (35µg/100ml breath) and
performance was studied in control conditions and whilst using a hand-held and a handsfree phone.
Figure 4: Reaction time to emergency events
Figure 4 shows reaction time to emergency events that were introduced into the simulated
driving context. Moving from left to right an increase in reaction time can be seen. In the
control condition drivers were typically able to react to the emergency events in just under a
second. Next is shown the alcohol condition in which drivers were typically able to react in
just over a second. However, significantly slower was the hands-free condition (50 % slower
than Control and 30 % slower than Alcohol) and slower again was the hand-held condition
(although the two phone conditions did not differ significantly).
It has generally become socially unacceptable to drink and drive – this research suggests that
using a mobile phone whilst driving places the driver in a similar state as one who is over
the legal limit of alcohol. However, it has to be pointed out that the characteristics of
impairment are entirely different and the driver can choose to terminate the phone-related
impairment much more rapidly than discharging the effects of alcohol.
TRL Study on Conversations in Cars
This work was undertaken by TRL for the UK Department of Health (Parkes et al., 2007). The
report contains a summary of previous UK research and a review of international research. It
Collective Expert Report
- 182 -
13/12/2011
also describes a driving simulator study comparing three conditions to controls: talking on a
hands-free phone, talking to a passenger and using the radio and climate settings.
In summary, the following was observed and quantified concerning phone conversations:
•
Slower speed and increased speed variation
•
More drifting in lane
•
Slower reaction time
•
More missed events
•
Poorer decision making
• Consistently worse performance with phone conversation than with passenger
conversation
• Phone conversations were rated by participants as higher workload than talking to
passenger
Interestingly, when conversing, more time was spent looking ahead, but this actually
reduced the number of events detected implying that situation awareness was reduced and
that too much attention is focussed on the conversation.
TRL Study on Texting while Driving
This study by TRL was carried out for the RAC foundation (Reed and Robbins, 2008). It was
the first UK study of its kind and attracted extensive media coverage.
Figure 5 shows the difference in reaction times between control conditions of driving and
driving while texting to auditory and visual stimuli.
Figure 5: Reaction time
Probably the most dramatic effects were observed in lateral control of the vehicle with lane
departures going from 4 in the control condition to 42 in the texting condition. This is shown
in Figure 6.
Collective Expert Report
- 183 -
13/12/2011
Figure 6: Lane departures
These results are compatible with those from the US Virginia Tech study of truck drivers
during real driving (Olsen et al., 2009). The study involved 200 vehicles covering 3 million
miles and involving 4,452 critical events. Overall, 81 % of events involved driver distraction
and the study found a 23× increased risk of event involvement when texting. Typically
drivers had their eyes off the road for four of every six seconds while texting.
Discussion of Future Options to Improve Safety
The results briefly outlined above illustrate that mobile phones present a distraction hazard.
This has been quantified by experiemetal trials and also observed during real driving. The
extent of the effect of phones appears large, but a key question is the actual impact on
accidents of different severity. The Virginia Tech study implies a high involvement in critical
events, but it is unclear how may phone related events actually lead to serious
consequences.The UK has approximately 3000 fatalities per year. Based on police reports
(and police investigation of fatalities is rather comprehensive), of these just 24 had mobile
phone as major contributory factor (0.8 %). So, evidence of major safety consequences is less
dramatic and, in policy terms, attempts to increase phone safety have to be balanced with
other road safety issues (such as alcohol, speed and seat belts, for example). One also has to
consider mobile phone usage within a broader context of in-vehicle devices. The technology
is evolving and merging and what is a “mobile phone” today may not be so clear tomorrow.
Legislation concerning companies (phone use while driving for work) appears to be broadly
effective for large organisations but probably less so for smaller ones and self-employed
individuals. Legislation concerning drivers themselves exists but clearly fails to stop all
illegal use.
For both “targets” it is unclear what the effect would be of more information messages,
greater enforcement and more serious penalties. In the UK there have been a series of rather
emotional and shocking information advertisements; the question is how often to repeat the
message?
Legislation on car manufacturers would be difficult because of evolution of the technology
and difficulties of enforcing equipment brought into a vehicle by the driver.
Some technology exists which could be used to identify a moving phone and then require
either confirmation that the user is not driving, or some dexterity test before the phone
became active. The practicality and effectiveness of such usage hurdles is questionable.
Collective Expert Report
- 184 -
13/12/2011
One positive point is that vehicles continue to become safer and so it can be expected that
secondary safety systems will increasingly protect the driver and other road users from their
own shortcomings.
Driver distraction is an area where further research is required. In a recent report (Basacik
and Stevens, 2008) TRL has attempted to summarise and critically review research on driver
distraction, both within and outside the vehicle; identify gaps in knowledge and has
proposed a programme of future research.
Dr Alan Stevens 23
Transport Research Laboratory, TRL Ltd, UK 24
REFERENCES
NARINE S, WALTER LK AND CHARMAN SC. Mobile phone and seat belt usage rates in London
2009. TRL Report PPR 418, Transport Research Laboratory, Wokingham, 2010
REDELMEIER DA, TIBSHIRANI RJ. Association between cellular mobile phone calls and motor
vehicle collisions. New England Journal of Medicine 1997, 336 : 453-458
BURNS PC, PARKES AM, BURTON S, SMITH, RK, BURCH D. How dangerous is driving with a
mobile phone? Benchmarking the impairment to alcohol. TRL Report TRL547, Transport Research
Laboratory, Wokingham, 2002
PARKES AM, LUKE T, BURNS PC, LANSDOWN T. Conversations in Cars-The Relative Hazards of
Mobile Phones. TRL Report TRL664, Transport Research Laboratory, Wokingham, 2007
REED N, ROBBINS R. The Effect Of Text Messaging On Driver Behaviour. TRL Report PPR367,
Transport Research Laboratory, Wokingham, 2008
OLSEN RL, HANOWSKY RJ, HICKMAN S, BOCANEGRA J. Driver Distraction in Commercial
Vehicle operations. Virginia Tech study for FMCSA, 2009
http://www.fmcsa.dot.gov/facts-research/research-technology/report/FMCSA-RRR-09-042.pdf
[accessed 12/05/10]
BASACIK D, STEVENS A. Scoping study of driver distraction. Road Safety Research Report No95,
October 2008. Department for Transport, 2008
23 Acknowledgements: The author is grateful to INSERM for financial support. The information contained in this paper is the
responsibility of the authors and does not necessarily represent the policy of any organisation.
24
© Transport Research Laboratory, 2010
Collective Expert Report
- 185 -
13/12/2011
Collective Expert Report
- 186 -
13/12/2011
Driver Distraction: Definition, Mechanisms, Effects and
Mitigation
Driving is a complex activity that involves the simultaneous performance of multiple subtasks–finding your way; following the road; monitoring your speed; avoiding collisions;
following traffic rules; and being in control of the vehicle (Brown, 1986, cited in Falkmer and
Gregersen, 2003). Despite this complexity, drivers can often be seen engaging in additional
activities that take their mind and eyes off the road, and their hands off critical vehicle
controls (e.g., the steering wheel; gear controls). There is converging evidence that distraction
is a significant contributing factor in crashes and critical incidents (Gordon, 2008).
The last decade has seen an explosion in research on driver distraction, culminating recently
in the publication of the first book on the topic (Regan et al., 2008a), a biannual international
conference series on driver distraction and inattention (Regan and Victor, 2009), and a
National Summit on distracted driving convened in September of 2009 and 2010 by the US
Transportation Secretary-Ray LaHood (e.g., DOT, 2009).
This paper does not focus specifically on driver distraction deriving from the use of mobile
mobile phones. Rather, it provides the reader with a general overview of the term “driver
distraction”: what it means; how it relates to other forms of driver inattention; types of driver
distraction; sources of driver distraction; factors that moderate the effects of distraction on
driving; the interference that can derive from distraction; theories that explain this
interference; the impact of distraction on driving performance and safety; and strategies for
the management of driver distraction as a road safety issue. The paper provides the reader
with a broad perspective from which to assess the role of distraction deriving from mobile
phone use as a road safety issue.
Driver Distraction-Definition
People talk about driver distraction as if they know what it means (Regan et al., 2008a);
however, as a scientific concept, it has been inconsistently defined. There is, in addition,
much confusion in the literature about the relationship between distraction and inattention.
Many research papers on driver distraction fail to define the very construct they purport to
investigate. The lack of an agreed definition is problematic, as it can make inter-study
comparisons difficult and can lead to vastly different estimates of the role of distraction in
crashes and near- crashes (Gordon, 2008).
Dictionary definitions of distraction vary somewhat, but are consistent in suggesting that
distraction involves a diversion of attention away from something toward something else.
Definitions of distraction, in the context of driving, are similarly diverse. The following is a
small sample of definitions, drawn from the literature, which illustrates this point. Definition
1 was derived by an assembled group of experts; Definitions 2 and 3 were derived from a
systematic review and analysis of definitions cited previously in the literature; and
Definition 4 was derived from the categorization of human failures observed as contributing
factors in in-depth analyses of crashes.
(1) “a diversion of attention from driving, because the driver is temporarily focusing on an
object, person, task or event not related to driving, which reduces the driver’s awareness,
Collective Expert Report
- 187 -
13/12/2011
decision making ability and/or performance, leading to an increased risk of corrective
actions, near-crashes, or crashes.“ (Hedlund et al., p. 2).
(2) “Driver distraction is the diversion of attention away from activities critical for safe
driving toward a competing activity” (Lee et al., 2008a).
(3) “Driver distraction:
Delay by the driver in the recognition of information necessary to safely maintain the lateral
and longitudinal control of the vehicle (the driving task) (Impact)
Due to some event, activity, object or person, within or outside the vehicle (Agent)
That compels or tends to induce the driver’s shifting attention away from fundamental
driving tasks (Mechanism)
By compromising the driver’s auditory, biomechanical, cognitive or visual faculties, or
combinations thereof (Type)”(Pettitt et al., 2005, p. 11).
(4) Driver distraction occurs “whenever a driver is delayed in the recognition of information
needed to safely accomplish the driving task, because some event, activity, object, or person
within [or outside] his vehicle, compelled or tended to induce the driver’s shifting of
attention away from the driving task” (Treat, 1980, p. 21)
These definitions, and the approaches taken in deriving them, reveal some key attributes
which have been thought about in defining driver distraction (Regan et al., 2010) :
• there is a diversion of attention away from driving, or activities critical for safe
driving ;
• attention is oriented toward a competing activity, inside or outside the vehicle, which
may be driving- or non-driving related ;
• the competing activity may compel or induce the driver to divert attention toward
itand ;
•
there is an assumption, implicit or explicit, that safe driving is adversely effected.
Driver Inattention-Definition
Driver inattention and driver distraction are related concepts. However, there is great
diversity of thinking in the literature about the nature of the relationship between them. Few
definitions of driver inattention exist, and those that do vary widely in meaning. The
following is a small sample of definitions, drawn from the literature, which illustrates this
point.
“….whenever a driver is delayed in the recognition of information needed to safely
accomplish the driving task, because of having chosen to direct his attention elsewhere for
some non-compelling reason”. (Treat, 1980, p21)
“…improper selection of information, either a lack of selection or the selection of irrelevant
information”. (Victor et al., 2008, p137)
“…diminished attention to activities critical for safe driving in the absence of a competing
activity” (Lee et al., 2008a, p32)
“low vigilance due to loss of focus” (Talbot and Fagerlind, 2009, p4)
“when the drivers’ mind has wandered from the driving task for some non-compelling
reason” (Craft and Preslopsky, 2009, p3)
Collective Expert Report
- 188 -
13/12/2011
Regan et al. (2010) have proposed a taxonomy of inattention that derives predominantly
from the analysis of in-depth crash data (in particular the work of Van Elslande and Fouquet,
2007 ; Treat, 1980) and from other lines of thinking deriving from the fields of human factors
and cognitive psychology. This taxonomy is shown in Figure 1. Regan et al. (2010) define
driver inattention as “insufficient or no attention to activities critical for safe driving” (p.16),
and argue that driver inattention arises from the following forms of inattention:
• Driver Restricted Attention (DRA) – “Insufficient or no attention to activities critical
for safe driving brought about by something that physically prevents (due to biological
factors) the driver from detecting (and hence from attending to) information critical for
safe driving” (p. 17)
• Driver Misprioritised Attention (DMA) – “Insufficient or no attention to activities
critical for safe driving brought about by the driver focusing attention on one aspect of
driving to the exclusion of another, which is more critical for safe driving” (p. 17)
• Driver Neglected Attention (DNA) – “Insufficient or no attention to activities critical
for safe driving brought about by the driver neglecting to attend to activities critical for
safe driving.” (p. 18)
• Driver Cursory Attention (DCA) – “Insufficient or no attention to activities critical for
safe driving brought about by the driver giving cursory or hurried attention to activities
critical for safe driving” (p. 19)
• Driver Diverted Attention (DDA) – “The diversion of attention away from activities
critical for safe driving toward a competing activity, which results in insufficient or no
attention to activities critical for safe driving”. (p. 19) As shown in Figure 1, the competing
activity toward which attention is diverted can be non-driving-related or driving-related.
Driver diverted attention is, in this taxonomy, synonymous with “driver distraction”.
Collective Expert Report
- 189 -
13/12/2011
Figure 1: Taxonomy of Driver Inattention (Source: Regan et al., 2010)
The above definition of driver distraction, proposed by Regan et al. (2010), although labeled
“driver diverted attention”, is almost identical to that previously coined for driver
distraction by Lee et al. (2008a) and carries the following assumptions:
•
it includes competing activities that can be driving and non-driving-related
• driver engagement in competing activities can be self-initiated or can occur
involuntarily
•
competing activities can derive from inside or outside the vehicle
• competing activities can include “internal” sources of distraction, such as
daydreaming and “task unrelated thought” (Smallwood et al., 2003)
• engagement in the competing activity can give rise to interference that is “manifest”
and observable (e.g. lane excursion) or “intrinsic and unobservable (e.g. loss of situational
awareness) (Hancock et al., 2008)
The following are some examples of driver distraction and other forms of inattention that
derive from the taxonomy proposed by Regan et al. (2010):
• Driver dozes off momentarily, with closed eyes, and almost hits a pedestrian crossing
the street ahead (driver restricted attention)
• Driver looks over their shoulder for too long while merging and fails to see a lead
vehicle rapidly braking (driver misprioritised attention)
Collective Expert Report
- 190 -
13/12/2011
• Driver neglects to scan to the left for approaching trains at a railway level crossing,
because he does not expect trains to be there (because they are rarely or never seen)
(driver neglected attention)
• Driver in a hurry does not complete a full head check when merging onto a highway
and collides with a merging car (driver cursory attention)
• Driver looks at cell phone while dialing a friend (driver diverted attention – nondriving related)
• Driver looks at unexpected flashing fuel warning light (driver diverted attention –
driving-related)
• Driver thinks about what needs to be done when he or she gets to work (driver
diverted attention – non driving related)
• Driver thinks constantly about where to find nearest service station, because the fuel
tank is almost empty (driver diverted attention – driving related)
• Driver daydreams about a romantic holiday in Paris (driver diverted attention – non
driving related)
The model proposed by Regan et al. (2010) assumes that it is not necessary for the driver to
have control over the factors that give rise to inattention. For example, biological factors
beyond the control of the driver (such as when the eyes of a drowsy driver close), may make
it difficult or impossible for a driver to attend to activities critical for safe driving. For this
reason, they include the ‘Driver Restricted Attention’ category within the model.
Regan et al. (2010) also consider the relationship between driver inattention and driver
conditions (e.g., young, inexperienced, etc) and between driver inattention and driver states
(e.g., bored, tired, lacking vigilance, sleepy, fatigued, drunk, drugged, medicated,
emotionally upset, etc). They argue (p. 23) that “driver conditions and states are factors that
can either (a) give rise to different forms of inattention (e.g., the young inexperienced driver
who fails to effectively prioritise attention when performing multiple driving activities; the
tired driver who experiences moments of vision loss due to blinking) or (b) moderate the
impact of a given form of inattention (e.g., the young driver who, as a result of inexperience,
is affected more by a competing activity because he or she has less spare attentional capacity
to devote to the competing activity).”
Finally, within the model proposed by Regan et al. (2010), inattention can mean either
insufficient or no attention to activities critical for safe driving. From the taxonomy in Figure
1, it is apparent that this can be brought about in different ways by different forms of
inattention.
Types of distraction
In the previous discussion, a distinction was made between driver distraction and other
forms of driver inattention. Driver distraction, itself, can be further decomposed into subcategories. Regan (2010) has distinguished between six different types of distraction, which
differ according to the sensory modality via which the diversion of attention toward a
competing activity is initiated:
•
diversion of attention toward things we see (visual distraction)
•
diversion of attention toward things that we hear (auditory distraction)
•
diversion of attention toward things we smell (olfactory distraction)
Collective Expert Report
- 191 -
13/12/2011
• diversion of attention toward things we taste (e.g., a rotten apple; gustatory
distraction)
• diversion of attention toward things we feel (e.g., a spider on our leg; tactile
distraction)
• diversion of attention toward things we think about (internal distraction) (often
referred to as “cognitive distraction”)
To date, distraction research has been confined to the understanding of the impacts of visual,
auditory and internal distraction.
Sources of distraction
Different sources of distraction, which can give rise to competing activity, have been
identified in the literature (see Regan et al., 2008a). These can be distilled into the following
broad categories:
•
objects (e.g., mobile phone; advertising billboard; apple)
•
events (e.g. crash scene; lightning)
•
passengers (e.g., child)
•
other road users (e.g., pedestrian; motorcycle rider)
•
animals (e.g., a moose)
• internal stimuli (i.e., deriving from within the mind - which may stimulate thought,
trigger observable actions such as coughing or sneezing, etc)
External sources of distraction (i.e., objects, events, passengers, etc) will be distracting only if
drivers interact with them, deliberately or involuntarily. A mobile phone, for example, is not
distracting unless a driver uses it or hears it when it rings; passengers will be distracting only
if the driver interacts with them, or reacts in some way to their mere presence. The same
source of distraction can induce different types of distraction. An advertising billboard, for
example, will induce visual distraction if the driver looks at it. If the driver thinks about the
message that it conveys, this will generate internal distraction. Similarly, “use” of a mobile
phone can mean many things – looking at it; using it to dial a number or send a text message;
using it to read a text message; listening to it; etc. Each of these different modes of interaction
will generate different types of distraction, individually or in combination, which will in turn
generate different patterns of interference (see below).
Moderating Factors
Whether distraction, when it occurs, impacts on performance and safety depends on four
main factors (Young et al., 2008): driver characteristics; driving task demand; competing task
demand; and the ability of the driver to self-regulate in response to the competing activity.
Driver characteristics include age, gender, driving experience, driver state (e.g., drowsy,
drunk, angry, upset), familiarity with and amount of practice on the competing task,
personality (e.g., risk taking), and ones’ vulnerability to distraction. An inexperienced driver,
for example, will have less attention available to divert to a competing task than an
experienced driver who, through practice and experience, has learned to automate many
driving sub-tasks and hence requires less attention to perform them.
Collective Expert Report
- 192 -
13/12/2011
Factors which influence driving task demand include traffic conditions, weather conditions,
road conditions, the number and type of vehicle occupants, the ergonomic quality of cockpit
design, and vehicle speed. Generally, the lower the demand of driving, the greater will be
the residual attention available to attend to competing activities. A well ergonomically
designed vehicle cockpit, for example, which minimises workload, will give the driver more
capacity to attend to competing tasks, and hence reduce interference between the tasks.
Given that modern driving does not require complete and continuous attention to maintain
safe driving performance – that it is a “satisficing task” (Hancock et al, 2008) – the often low
demands of driving may encourage drivers to allocate attention to information irrelevant to
safe driving.
The demands of the competing task will have a critical bearing on the degree of interference
it brings about. Factors that influence competing task demand include how similar it is to
driving sub-tasks (e.g., whether it requires vision or control actions similar to those required
to control the car), its complexity, whether it can be ignored, how predictable it is, how easily
it can be adjusted, how easily performance of it can be interrupted and resumed, and how
long it takes to perform. The longer a driver is exposed to a source of distraction that
interferes with safe driving, the greater will be its impact.
Finally, the ability of the driver to self-regulate will have a critical bearing on whether it
distracts the driver. Self-regulation at the strategic, tactical and operational levels of driving
control can be exercised by drivers to control exposure to competing activities, to regulate
the timing of the engagement, and to control resource investment (Lee et al., 2008b). There
are times, however, when self-regulation might not be possible, even though it is what the
driver wants. Social and business imperatives that require a driver to use a mobile phone at
times that the driver would not otherwise choose to do so is such an example.
Although these factors moderate the effects of distraction, they are rarely controlled for in
experimental studies. Yet they are important independent variables in any study of
distraction. This makes it difficult, and often impossible, to compare across studies the
impact on behaviour and performance of different sources of distraction.
Interference
If a driver is distracted, performance of the competing task will interfere in some way with
activities critical for safe driving. This interference can be minimal or significant. The four
moderating factors, described above, can be seen as regulating the amount of interference
between the competing task and activities critical for safe driving. The effects of the
interference, as noted, may be manifest and observable (as in a lane excursion) or intrinsic
and unobservable (as in a loss of situation awareness). (Hancock et al., 2008). At present, we
know little about intrinsic interference, but one can imagine that it can lead to errors in the
minds of drivers at different stages of information processing (from perception through to
action; Horrey WJ, personal communication, 7 May 2010) which may or may not result in
manifest interference.
Theories of Interference
Distraction is a problem for drivers because their ability to divide attention between
competing tasks is fundamentally limited by their biological makeup. Broadly speaking,
Collective Expert Report
- 193 -
13/12/2011
there are three psychological accounts of the mechanisms that give rise to this interference –
multiple resource theory, single channel theory and control theory.
Multiple resource theories of attention (Wickens, 1992) propose that a competing activity will
interfere with tasks critical for safe driving if the two activities:
•
share common perceptual modalities (auditory versus visual)
•
share common processing codes (verbal versus spatial)
•
share common processing stages (perceptual-cognitive-motor)
•
share common modalities of output (manual vs vocal)
•
share common “visual channels” (focal versus ambient)
•
are mutually demanding.
According to this theory, attention can be divided between competing tasks provided that
they are sufficiently different from one another in their structural characteristics, and do not
demand more attention than is available.
Single channel theories (Broadbent, 1958) imply that attention cannot be divided between
competing tasks. If two tasks compete for attention at the same time, or very close in time,
they must be performed one at a time. Simultaneous performance of the tasks can only be
accomplished by rapid switching of attention between them. According to this theory
competing activity will interfere more with tasks critical for safe driving under the following
conditions (which are not all mutually exclusive):
• if the two activities share the same stage of information processing (e.g. response
selection)
• if they cannot be inter-digitated (if aspects of one activity cannot be accomplished
during time gaps left vacant by the other)
• if they cannot be coordinated in time (as when one “rubs ones’ stomach while patting
ones’ head”)
• if information from the competing task cannot be “chunked” into smaller units of
information
•
if the competing task is high in task demand
•
if the competing task is unpredictable
•
if the competing task is unpractised
Control theory asserts that drivers actively control the level of distraction they experience.
This control is assumed to occur at three levels of driving control (strategic, tactical and
operational) - each with different time horizons - and is achieved by three types of control
(feedback, feed forward and adaptive) (Lee et al., 2008a). The limits of control at each level,
and the interactions between failures at these levels, cause distraction-related mishaps.
According to this theory, the key mechanisms that mediate the degree of interference
between driving and competing tasks are the “ignorability”, predictability,
“interruptability”, and “adjustability” of the task(s) that compete for the driver’s attention
(Lee et al., 2008a).
Collective Expert Report
- 194 -
13/12/2011
Impact on driving Performance
Having defined driver distraction, and the mechanisms that give rise to interference when a
driver is distracted, it is appropriate to consider the impact that this interference may have
on driving performance. Various driving performance deficits have been reported for
different competing activities. Reported deficits vary and include (Bayley et al., 2008;
Horberry et al., 2008) degraded lane keeping, degraded speed control, increased reaction
time, missed traffic signals, shorter or longer inter-vehicle following distances, unsafe gap
acceptances, reduced situation awareness, poorer visual scanning, reduced horizontal field
of view and missed checks (e.g., mirror checks).
The nature and magnitude of the performance deficits that arise depend on the moderating
factors already described (i.e., driver characteristics; driving task demand; competing task
demand; and the ability of the driver to self-regulate in response to the competing activity).
Certain characteristics of the competing task are particularly important in this respect (Victor
et al., 2008). Tasks that are primarily visually distracting, and hence take the eyes (and to a
lesser extent the mind) off the road tend to degrade to a greater extent lane keeping
performance and event detection. Tasks that primarily take the mind off the road (e.g., a
complex cell phone conversation using a hands-free device) tend to increase road-centre
viewing time, spatially concentrate gaze on the forward road centre at the expense of
peripheral glances, and may sometimes even improve lane keeping performance. Generally,
delays in event detection are greater for tasks that are visually distracting than for those that
are primarily cognitively demanding (see Victor et al., 2008, for a review of these findings).
Driving performance deficits have been reported in the presence of competing activities
deriving from use of mobile mobile phones, iPods, DVD players, navigation systems, email
systems, radios and CD players. Driving performance deficits have also been reported for
drivers that engage in everyday activities such as eating, drinking, smoking, reading,
writing, reaching for objects, grooming themselves, and interacting with passengers (see
Bayley et al., 2008, for a review of findings).
Impact on Safety
It is beyond the scope of this paper to review in detail the state of the art on the impact of
driver distraction on driver safety. A few key points will be made.
Gordon (2008) reviewed a number of studies - in the United Sates and New Zealand - that
used police reports or findings from crash investigation teams to provide information on a
wide range of inside-and outside-the vehicle distractions believed to have contributed to
crashes. The studies reviewed by Gordon consistently identified driver distraction as a
contributing factor in 10 to 12% of crashes, and about one-fifth of these crashes involved
driver interaction with technology.
Police-reported data tend to underestimate the true magnitude of the distraction problem,
for a variety of reasons (Gordon, 2008). Data from “naturalistic driving studies” (Klauer et
al., 2006; Olsen et al., 2009) present a more accurate picture of the role of distraction in
crashes and incidents. In such studies, instrumented vehicles, equipped with video cameras
and other sensors, are used to record driver and driving behaviours continuously, over
periods of weeks, months and even years. Episodes of driver distraction which are
observable on video can then be identified, characterised and counted. These studies suggest
Collective Expert Report
- 195 -
13/12/2011
that up to 22% of car crashes and 71% of truck crashes involve as a contributing factor
distraction from non-driving-related activities (Klauer et al., 2006; Olsen et al., 2009).
Epidemiological studies, which include naturalistic driving studies, enable researchers to
calculate estimates of increased risk. McEvoy and Stevenson (2008) reviewed a wide range of
epidemiological studies, including a study that used vehicles with cameras and other sensors
to observe driver behaviour (the so-called 100-car naturalistic driving study; Klauer et al.,
2006) and identified several key sources of driver distraction which have been shown to
significantly elevate crash risk, including mobile phone use. In relation to mobile phone use,
they conclude (p. 314) that:
“…mobile phone use while driving has been shown to be associated with an increased risk
of crashing, including property-damage only and injury crashes, as well as at-fault nearcrashes. Risk estimates in studies that have phone activity records or video evidence of
phone use at the time of the crash are generally between three- and fourfold. The risk of
crashing appears to be increased whether or not a hands-free device is available for use in
the vehicle. Further research to examine whether certain types of hands-free devices are safer
than others is warranted. However, given that hands-free devices do not eliminate certain
distracting effects, namely, those relating to the act of conversing, it is doubtful that any
device will be free of risk. If one type of device is found to be safer (but not free of risk), its
increased use may paradoxically increase the number of crashes associated with phone use,
as the impact of a risk factor on road safety is a function not only of the risk estimate but also
the prevalence of use “.
The data that emerge from naturalistic driving studies provide the most detailed
comparisons of changes in risk associated with driver engagement in different distracting
activities.
Olsen et al. (2009), from VTTI in the United States, investigated the prevalence of driver
distraction in 4,452 safety-critical events (i.e. crashes, near-crashes) involving commercial
trucks instrumented with video and other vehicle sensors and recording devices. Safetycritical events were recorded in a data set that included 203 drivers and 3 million miles of
data. Truck drivers were found to be engaged in “tertiary” (i.e., non-driving related)
activities in 71 percent of crashes, 46 percent of near-crashes and 60 percent of all safetycritical events. Drivers were X times (see below) more likely to be involved in a safety-critical
event while performing the following activities: text messaging – 23 times; using a
dispatching device - 9.9 times; writing – 9.0 times; using a calculator – 8.2 times; looking at a
map – 7.0 times; reaching for an electronic device – 6.7 times; dialing a hand-held cell phone 5.9 times; personal grooming – 4.5 times; and reading - 4.0 times. Tasks that drew the
driver’s eyes away from the forward roadway had the highest risk of a safety-critical event.
Tasks with the largest Population Attributable Risk (PAR) Percentages (i.e. which are
estimates of the proportion of crashes attributable to a source of distraction) were: reaching
for an object (PAR = 7.6); interacting with a dispatching device (PAR = 3.1); and dialing a
hand-held cell phone (PAR = 2.5). Text messaging, although it had a very high risk estimate,
was a task performed infrequently by truck drivers and thus did not have a high PAR
percentage (only 0.7). However, as texting while driving a truck becomes a more prevalent
activity, the frequency of safety-critical events is likely to increase, and so too will risk.
A precursor study, involving ordinary passenger cars, is also worth highlighting. The
seminal 100-car naturalistic driving study by Klauer et al. (2006; noted above) involved 100
instrumented cars and 241 drivers. It collected 2,000,000 vehicle miles, or 43,000 hours, of
data over a 12 to 13 month period. Here, 78% of crashes and 65% of near-crashes involved
inattention as a contributing factor. Distraction (defined as driver engagement in non-driving
related activities) was a factor in 22% of crashes. Drivers were X times (see below) more
Collective Expert Report
- 196 -
13/12/2011
likely to be involved in a crash or near-crash while performing the following activities:
reaching for a moving object - 8.8 times; looking at an external object - 3.7 times; reading –
3.38 times; applying makeup - 3.1 times; dialing a hand-held device - 2.8 times; and listening
to a hand-held phone - 1.3 times (although the latter increase was not significantly different
from 1.0.). The highest PAR percentages, however, were obtained for dialing a hand-held
device (3.6), talking on a hand-held device (3.6), and reading (2.9).
Managing Distraction
It is not possible to eliminate distraction. At best, it can be effectively managed. Regan et al.
(2008b) have estimated that 55% of all known sources of distraction are avoidable (61% of
sources from within the vehicle and 31% of sources outside the vehicle). Countermeasure
development for distraction is still in its infancy, even in countries like Sweden with
relatively good safety records. This is not surprising, as systems for accurately and reliably
collecting and analyzing data on the role of distraction in crashes do not exist in most
countries.
Regan et al. (2008c) have recommended numerous countermeasures for preventing
distraction or mitigating its effects, under each of the following general categories: Data
collection; Education; Company car fleet management; Legislation; Enforcement; Driver
licensing; Road and traffic design; Driver training; and Vehicle Design. Ultimately, the goal
of the road safety community should be to design a distraction-tolerant road system in which
no one involved in a distraction-related crash is killed or seriously injured (Tingvall et al.,
2008). This requires countermeasures that support drivers at all stages of the crash sequence
– that support them, for example, to drive normally (e.g. intelligent speed adaptation); to
warn them if they deviate from normal driving (e.g. real-time distraction warnings); to
support them in emerging situations (e.g. lane keeping assist); to help them, and the car,
avoid a crash (e.g. automatic brake assist); and, where a crash is unavoidable, to ensure that
the speed of the vehicle and the legal speed limit are in accordance with the capacity of the
vehicle and the infrastructure to protect them and their occupants from serious injury.
Real-time, vehicle-based, distraction countermeasures have perhaps the greatest potential to
manage distraction. They can adaptively prevent or limit driver exposure to competing tasks
when the concurrent demands of driving are estimated to be high (real-time distraction
prevention; e.g., “workload managers”) – and they can mitigate the effects of distraction
once it occurs, by providing feedback and warnings to drivers that re-direct their attention to
relevant aspects of the driving task (real-time distraction mitigation; e.g. “distraction
warning systems”) (Victor et al., 2008). These systems can detect whether a driver is
distracted, regardless of the competing activity (driving- or non-driving related), regardless
of whether driver engagement in the competing activity is voluntary or involuntary,
regardless of whether the competing activity derives from inside or outside the vehicle, and
regardless of whether the distraction is visual, internal or is of some other type (e.g.,
auditory). Furthermore, these systems can be optimized so that they are adaptive to factors
that moderate the effects of distraction (e.g., driver state) by, for example, issuing more
conservative warnings if the driver is drunk. Systems can also be used to prime and activate
the operation of other active and passive safety systems at different stages of the crash chain
to optimize driver safety during all stages of the crash sequence. Through the provision of
real-time feedback to drivers, these systems can also serve to train drivers automatically to
know when they are becoming distracted.
Collective Expert Report
- 197 -
13/12/2011
Conclusion
In this paper, driver distraction has been defined, characterised, and distinguished from
other forms of driver inattention. The paper provides background information suitable in
understanding and interpreting the potentially distracting effects on driving of using mobile
phones. Some concluding comments are made which pertain in particular to mobile phone
use while driving.
The mobile mobile phone is only one potential source of driver distraction. However, it can
be used to access and perform a variety of different functions. Each function requires
different driver-phone interactions (looking, listening, manipulating, etc), which in turn
generate different types of distraction (visual, auditory, etc). The different types of
distraction can in turn generate different patterns of interference, the magnitude of which
depends on four key moderating factors: driver characteristics; driving task demand;
competing task demand; and the ability of the driver to self-regulate in response to the
competing activity. Presently, little is known about the effects of driver characteristics and
driving task demand in moderating the impact on driving of competing activities, including
mobile phone use.
Not all mobile phone functions, and their effects on driving performance, have been
explored. The data reviewed in this paper suggest that, for the phone-related activities that
have been explored, use of a mobile phone generally increases crash risk for drivers of
passenger cars. The size of the increase in risk, however, depends critically on the phonerelated activity being performed.
Two recent naturalistic driving studies have yielded data suggesting that conversing on a
cell phone does not significantly increase crash risk (Klauer et al., 2006; Olsen et al., 2009),
which is in conflict with findings from previous epidemiological studies. Indeed, the
findings from the Olsen et al study (involving truck drivers) suggest that conversing on a
hands-free phone (or a hand-held CB radio) actually reduces crash risk. The mechanism for
this latter decrease in risk is presently unknown. It may be, following from earlier discussion,
that certain moderating factors reduce the impact of distraction for professional drivers.
Generally they are more experienced than normal drivers, and are more practiced in timesharing between driving and operating other in-vehicle systems (CB radios, dispatching
systems) that are considered to be “part of the job”. This, however, does not explain the
apparent protective effect of conversing for truck drivers. Presumably, conversing on a
hands-free phone or via a CB radio reduces the likelihood of drowsy truck drivers having
drowsiness-related crashes. Conversing on the phone likely keeps them awake, but this is yet
to be confirmed. The naturalistic driving study is still a relatively new research method and,
although the finding is interesting and controversial, the limitations of the data from studies
that use this method must be understood. McEvoy and Stevenson (2008; p. 316), for example,
have highlighted certain limitations pertaining to the 100-car study, which are also relevant
to the naturalistic truck driving study:
“the relatively small, non representative, volunteer sample; the difficulty in reliably
capturing some types of secondary distracting tasks, such as drivers’ level of cognitive
attention, the role of passengers (for privacy reasons), and some outside distractions; issues
with inter-rater reliability in coding distracting activities and assigning fault for crashes and
near-crashes; and a lack of data on the role of driver distractions in more serious crashes
resulting in driver injury.”
The outcomes considered in these two naturalistic driving studies are almost entirely critical
incidents - not crashes. It is currently unknown whether the increased risk associated with a
distraction-related critical incident in which a crash was avoidable is comparable to that for a
Collective Expert Report
- 198 -
13/12/2011
critical incident in which the crash was unavoidable. In addition, as noted by the
epidemiological expert who has given separate evidence to this expert committee, there are
problems associated with the calculation of the confidence intervals for the odds ratios
derived in these studies (which has implications for the significance of different odds ratios);
and there is no multivariate analysis of the data. Given these limitations, it is difficult to
know at this point in time how much weight can be put on the finding from the two studies
that conversing on a mobile mobile phone (hand-held or hands-free) does not significantly
increase crash risk. A much larger naturalistic driving study currently being conducted in the
US (involving more than 3000 volunteer drivers; see www.TRB.org/SHRP2) as part of the
second US Strategic Highway Research Program (SHRP2) will shed more light in this
finding.
Given that the mobile phone is a flexible platform that is capable of hosting a range of
relatively low-cost functions that have potential to support the driving task and enhance
safety (e.g., satellite navigation, intelligent speed adaptation), and given that when used to
converse it may have some unexpected safety benefits (subject to the caveats stated above;
for example, in mitigating the effects of drowsiness in truck drivers), it would seem
premature at this point in time to implement a total societal ban on its use while driving;
although in some jurisdictions, like the State of Victoria in Australia, it is noteworthy that a
total ban on the use of mobile phones while driving has been imposed on newly licensed
drivers. As Regan et al. (2008c, p545) have pointed out, “Further research is needed to
determine new ways of limiting levels of distraction associated with mobile phone use (e.g.,
through better design and by supporting use of it with real-time distraction prevention and
mitigation countermeasures), for all functions that can be accessed when using the device
while driving, and in exploiting the potential of the devices to host functions that have
potential to assist the driver and enhance safety. Such activity might help to bring together
vehicle manufacturers, aftermarket suppliers and nomadic device developers in achieving
the common goal of optimizing driver safety.”
Michael A. Regan, PhD
Research Director, INRETS, France
REFERENCES
BAYLEY M, REGAN MA, YOUNG K. Sources of distraction inside the vehicle and their effects on
driving performance. In: Driver distraction: Theory, Effects and Mitigation. Florida, USA, CRC Press,
Chapter 12, 2008
BROADBENT DE. Perception and communication. London, Permagon Press, 1958
BROWN ID. Functional requirements of driving: Paper presented at the Berzelius symposia Cars and
Casualties. Stockholm, 1986. Cited by FALKMER T, GREGERSON NP. The Trainer Project-the
evaluation of a new simulator-based driver training methodology. In: DORN L (ed). Driver behaviour
and training. England, UK, Ashgate, 2003: 317-330
CRAFT RH, PRESLOPSKY B. Driver Distraction and Inattention in the USA Large Truck and National
Motor Vehical Crash Causation Studies. First International Conference on Driver Distraction and
Inattention. 2009, 28-29 September http://document.chalmers.se/doc/589106931
DOT.
Department
of
Transportation
Distracted
http://www.tvworldwide.com/events/rita/090830/
Driving
Summit.
2009
GORDON CP. Crash studies of driver distraction In: REGAN MA, LEE JD, YOUNG KL (eds). Driver
Distraction: Theory, Effects and Mitigation. Boca Raton. FL CRC Press Taylor & Francis Group, 2008:
281-304
Collective Expert Report
- 199 -
13/12/2011
HANCOCK PA, MOULOUA M, SENDERS JW. On the Philosophical Foundations of the Distracted
Driver and Driving Distraction. In: REGAN MA, LEE JD, YOUNG KL (eds). Driver Distraction:
Theory, Effects, and Mitigation. Boca Raton. FL CRC Press Taylor & Francis Group, 2008: 11-30
HEDLUND J, SIMPSON H, MAYHEW D. International Conference on Distracting Driving: Summary
of Proceedings and Recommendations. Toronto, Canada, 2005, 2-5 October
HORBERRY T, EDQUIST J. Distractions outside the vehicle. In: REGAN MA, LEE JD, YOUNG KL
(eds). Driver Distraction: Theory, Effects, and Mitigation. Boca Raton. FL CRC Press Taylor & Francis
Group, 2008: 215-228
KLAUER SG, DINGUS TA, NEALE VL, SUDWEEKS JD, RAMSEY DJ. The Impact of Driver
Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study
Data. Report No DOT HS 810 594, National Highway Traffic Safety Administration, Washington, DC,
2006
LEE JD, YOUNG KL, REGAN MA. Defining Driver Distraction. In: REGAN MA, LEE JD, YOUNG KL
(eds). Driver Distraction: Theory, Effects, and Mitigation. Boca Raton. FL CRC Press Taylor & Francis
Group, 2008a: 31-40
LEE JD, REGAN MA, YOUNG KL. What drives distraction? Distraction as a breakdown of multilevel
control. In: REGAN MA, LEE JD, YOUNG KL (eds). Driver Distraction: Theory, Effects, and
Mitigation. Boca Raton. FL CRC Press Taylor & Francis Group, 2008b: 41-56
MCEVOY S, STEVENSON M. Epidemiological research on driver distraction. In: REGAN MA, LEE
JD, YOUNG KL (eds). Driver Distraction: Theory, Effects, and Mitigation. Boca Raton. FL CRC Press
Taylor & Francis Group, 2008: 305-318
OLSON RL, HANOWSKI RJ, HICKMAN JS, BOCANEGRA J. Driver distraction in commercial vehicle
operations. Report No. FMCSA-RRR-09-042, US Department of Transportation, Washington, DC, 2009
PETTITT M, BURNETT G, STEVENS A. Defining Driver Distraction. Proceedings of the 12th ITS
World Congress. San Francisco, USA, ITS America, 2005
REGAN MA. Driven by distraction. Vision Zero International. January, 2010. Ukip. Surrey, UK, Media
and Events Ltd, 2010: 4-12
REGAN MA, VICTOR T. Proceedings of the First International Conference on Driver Distraction and
Inattention. Gothenburg, Sweden. 2009, 28-29 September
REGAN MA, LEE JD, YOUNG KL. Driver Distraction: Theory, Effects and Mitigation. Boca Raton. FL
CRC Press Taylor & Francis Group, 2008a
REGAN MA, YOUNG KL, LEE JD, GORDON C. Sources of driver distraction. In: REGAN MA, LEE
JD, YOUNG KL (eds). Driver Distraction: Theory, Effects and Mitigation. Chapter 16, Boca Raton.
FL,CRC Press Taylor & Francis Group, 2008b
REGAN MA, YOUNG KL, LEE JD. Driver distraction injury prevention countermeasures: Part 1-Data
collection, legislation and enforcement, vehicle fleet management and driver licensing. In: REGAN
MA, LEE JD, YOUNG KL (eds). Driver distraction: Theory, Effects and Mitigation. Florida, USA, CRC
Press, 2008c: 533-558
REGAN MA, YOUNG KL, LEE JD. Conclusions. In: REGAN MA, LEE JD, YOUNG KL (eds). Driver
distraction: Theory, Effects and Mitigation. Florida, USA, CRC Press, Chapter 34, 2008d: 621-629
REGAN MA, HALLETT C, GORDON C. Driver distraction and inattention: Definition, relationship
and taxonomy. Manuscript submitted to Accident Analysis and Prevention on 17 November, 2010
SMALLWOOD J, BARACAIA SF, LOWE M, OBONSAWIN M. Task unrelated thought whilst
encoding information. Consciousness & Cognition 2003, 12(3): 452-484
TALBOT R, FAGERLIND H. Exploring inattention and distraction in the safetynet accident causation
database. First International Conference on Driver Distraction and Inattention. 2009, 28-29 September
http://document.chalmers.se/doc/589106931
Collective Expert Report
- 200 -
13/12/2011
TINGVALL C, ECKSTEIN L, HAMMER M. Government and industry perspectives on driver
distrcation. In: REGAN MA, LEE JD, YOUNG KL (eds). Driver Distraction: Theory, Effects, and
Mitigation. Boca Raton. FL CRC Press Taylor & Francis Group, 2008: 603-618
TREAT JR. A Study of Precrash Factors involved in Traffic accidents. The HSRI Review 1980, 10(1) : 135
VAN ELSLANDE P, FOUQUET K. Typical human functional failure-generating scenarios: A way of
aggregation. Deliverable D5.3. WP5 "Human factors". TRACE European project, 2007
VICTOR TW, ENGSTROM J, HARBLUK JLY. Distraction assessment methods based on visual
behaviour and event detection. In: REGAN MA, LEE JD, YOUNG KL (eds).Driver Distraction: Theory,
Effects, and Mitigation. Boca Raton. FL CRC Press Taylor & Francis Group, 2008: 135-165
WICKENS CD. Engineering psychology and human performance. NY HarperCollins, 1992
YOUNG KL, REGAN MA, LEE JD. Factors moderating the impact of distraction on driving
performance and safety. In: REGAN MA, LEE JD, YOUNG KL (eds). Driver Distraction: Theory,
Effects, and Mitigation. Boca Raton. FL, CRC Press Taylor & Francis Group, 2008: 335-352
Collective Expert Report
- 201 -
13/12/2011
Collective Expert Report
- 202 -
13/12/2011
Point of view of the Laboratory of accidentology and
biomechanics (LAB)
The Laboratory of accidentology and biomechanics (LAB) is a laboratory shared by two
French automobile manufacturers. It has national and international accidentological
databases (Gidas for the German In-Depth Accident Study; CCIS for Co-Operative Crash Injury
Study; Irtad for International Road Traffic and Accident Database) as well as its own database.
The latter relates more particularly to targeted studies and detailed accident studies.
Current data on accidents does not make it possible to assess whether or not the cell phone
would have an influence on the frequency of the occurrence of accidents due to the absence
of this data in current accident databases.
No direct objective data is therefore available.
Do cell phones currently induce a substantial road risk?
The decreasing curves in French accidentology are not in favor of such a hypothesis.
Moreover, a recent study of some American insurers on the link between the occurrence of
accidents and the ban on cell phones while driving did not make it possible to show an effect
of the ban 25 . This macroscopic study compares the change in accidentology between the
states with a cell phone and those without.
In her study of the modified case-control type (case-crossover design) of 2005, Mac Evoy et al.
(2005) find that the use of cell mobile phones when driving induces a risk multiplied by 4 of
having an accident. However, in their study, several points are in favor of an over-evaluation
in relation to the general population. The population studied is a population of drivers with
much distance due to the selection criteria for the sample. This bias is not taken into account
in estimating the risk. Moreover, due to the shortness of the mobile phone call, the
probability of having a mobile phone call during the very short controlled periods is low.
This artificially reduces the percentage of mobile phone calls in the control periods and
increases the risk of the cell phone during accidents. A control variable such as the
occurrence of at least one mobile phone call while driving during the travel corresponding to
the time bracket during which the accident occurred would seem to be more adapted.
Note that in this study, only 6% of the vehicles are equipped with a built-in hands-free kit
with voice control and the risk that is associated with them could not be specifically
evaluated.
This study is compared in 2007 with case-control studies on the influence of the presence of a
passenger on the risk of an accident (Mac Evoy et al., 2007). The subjects are people aged 17
and up that have had an accident and who were admitted to the hospital. They were
questioned in particular on the presence or not of passengers and how many there were. The
controls are the people contacted at petrol stations during business days and hours. The
study shows a risk of 1.6 for the risk of an accident when there are passengers. The risk
increases with the number of passengers. Other than the populations of the two studies
25
http://www.iihs.org/news/rss/pr012910.html
Collective Expert Report
- 203 -
13/12/2011
being very different, the second study does not take the effect of prevalence into account.
This point is discussed by Mac Evoy: "Although the risk associated with transporting
passengers is lower than that associated with using the cell phone, it is likely that the risk
that can be attributed to passengers is higher due to the high prevalence".
The cell phone does stand out particularly in relation to the other causes of distraction in the
car. This is confirmed by an American study on the sources of distraction during automobile
driving carried out in 2003 in the United States (Stutts et al., 2003). As changes in habits are
cultural and very quick, it would be important to be able to have such a study in France in
2010.
How does telephoning while driving induce distraction?
It is important to continue correctly distinguishing between telephoning while driving
without a hands-free kit and telephoning with a hands-free kit keeping in mind that there are
different types of hands-free kit that or more or less built-in ranging from the poorly-adapted
earpiece to the fully integrated system with voice control.
When one is behind the wheel in the car, the task of driving is the main task. This task does
not require all of the attentional resources in most cases. This is what allows the driver to
have a discussion with passengers, listen to the radio, look at the scenery and sometimes to
get lost in his thoughts to the point of driving in an "automatic" mode. In these situations, as
during a mobile phone conversation while driving, the driver is in a situation of shared
attention. This is not a problem at all, as long as the attentional resources dedicated to the
main task are sufficient, i.e. that the secondary task does not require attentional resources
that will amputate those initially dedicated to the main task. Ordinary automobile driving in
most cases allows for a secondary task in a modality that is other than visual, as this sensory
modality is already particularly solicited by the main task. However, the cognitive load can
vary substantially according to the context. It also depends on the driving experience of the
person. An experienced person will anticipate situations better. This person will also
automate certain activities. As such, for the same workload, the experienced driver will
mobilize much less attentional resources that a novice driver will. Moreover, the attentional
demand of the secondary task will depend on several factors: the sensory modality of the
secondary task, the complexity of this task, the adding of other secondary tasks. These points
make the difference between the mobile phone without a hands-free kit and one with a
hands-free kit. The fact of having to dial, handle driving with a single hand generates a
substantial increase in terms of cognitive demand and therefore for attentional resources.
Several points can be discussed concerning the experiments that do not conclude any
difference between hand-held mobile phones and hands-free kits: the type of hands-free kit
used to carry out the experiment or the finesse of the methodology used. Indeed, it is
difficult to think that there is no difference in additional load between saying "call Mr. X" via
voice control (pre-recorded name on a list) and having to type the number on a numeric
keyboard then having to handle driving with a single hand. Hands-free kits make it possible
to remain almost exclusively in an auditive modality and to enter into competition much less
with the task of driving than when using the mobile phone without a kit. At this stage, it is
important to correctly consider the fact that there are many hands-free kits that are different
from an integration standpoint.
It is this major difference which justifies the current regulations. If the regulations were to
become stiffer, this could be on the requirements to that hands-free kits have to fulfill.
Collective Expert Report
- 204 -
13/12/2011
Finally, the studies bring to the forefront the distractive effects of the mobile phone and often
take "focused on the road" driving as the "ideal" reference. Yet, reality is completely different:
distractions of exogenous origin via advertizing posters, messages of the highway, radio or
distractions of exogenous origin with continued reflection linked to diverse personal or
professionals situations.
What can automobile manufacturers propose?
Automobile manufacturers have worked and continue to work on better integration for the
cell phone in cars with, in particular, the improvement in audio quality, the development of
voice control, filtering of incoming calls and/or the setting up of messages informing the
caller that the person they are calling is in a driving situation.
It will also be possible to study limiting mobile phone use in a contextual way (for example,
when approaching an intersection).
Such improvements are obtained thanks to studies in experimental psychology and in
ergonomics carried out by the manufacturers. It would be a shame if these efforts are in vain
and we see the development of unauthorized uses of the mobile phone and of mobile
systems to the detriment of built-in systems.
Cell phones can also in certain cases favor easy driving. Identifying these effects is related
more to personal experience than to scientific data. Indeed, it does not seem possible at all to
quantify them. When one is late, being able to warn that one is going to be late and possibly
handling the problem is then accompanied by driving that is appeased and therefore less the
cause of accidents. Finally, in situations of drowsiness, conversing with someone makes it
possible to increase the level of vigilance.
In conclusion, a recent analysis carried out for the European Commission considers that it is
necessary to have additional elements in order to make a decision 26 .
It is certain that it would be interesting to be able to have direct accidentological data.
Anne Guillaume
Laboratory of accidentology and biomechanics (LAB)
GIE PSA Peugeot Citroën and Renault, Nanterre
BIBLIOGRAPHY
MCEVOY SP, STEVENSON MR, MCCARTT AT, WOODWARD M, HAWORTH C, et coll. Role of
mobile phones in motor vehicle crashes resulting in hospital attendance: a case-crossover study. BMJ
2005, 331: 428
MCEVOY SP, STEVENSON MR, WOODWARD M. The contribution of passengers versus mobile
phone use to motor vehicle crashes resulting in hospital attendance by the driver. Accident Analysis
Prevention 2007, 39: 1170-1176
STUTTS J, FEAGANES J, RODGMAN E, HAMLETT C, REINFURT D, et coll. The causes and
consequences of distraction in everyday driving. Annu Proc Assoc Adv Automot Med 2003, 47: 235-251
26
http://ec.europa.eu/transport/road_safety/pdf/car_mobile phone_use_and_road_safety.pdf
Collective Expert Report
- 205 -
13/12/2011
Collective Expert Report
- 206 -
13/12/2011
Appendix
Inserm collective expertise: Methodology
An Inserm collective expertise 27 sheds scientific light on a given subject in the field of health
on the basis of a critical analysis and synthesis of the international scientific literature. The
collective expertise is implemented at the request of institutions wishing for access to recent
research data pertinent to their decision-making process with respect to public policy. An
Inserm collective expertise is to be considered as an initial stage that is necessary but most
frequently not sufficient to result in decision-making. The conclusions of the collective expert
review contribute to, but cannot replace, debate between the professionals involved or
society debate if the questions addressed are particularly complex and sensitive.
At the request of an institution, the Inserm collective expertise may be accompanied by an
'operational' expertise addressing application of the knowledge and recommendations and
taking into account contextual factors (existing programs, structures, players, training, etc.).
The latter type of expert review elicits contributions from the players in the field able to
respond to the feasibility aspects, representatives of the administrations or institutions
responsible for promoting applications in the field involved, experts having contributed to
the reviews, and representatives of patient associations. The sharing of varied cultures and
experience enables a complementary approach to the collective expertise in an operational
framework. Moreover, a variety of work (recommendations for good practices, public
hearings, etc.) implemented under the auspices of the High Authority for Health (HAS) may
follow an Inserm collective expertise.
Collective expertise has been an Inserm mission since 1994. Some sixty collective expert
reviews have been implemented in numerous health fields. The Institute guarantees the
conditions under which the expert review is implemented (exhaustiveness of the document
sources, qualification and independence of the experts, transparency of the process).
The Inserm Centre for Collective Expertise organizes the various stages of collective
expertise from the initial problem statement through to communication of the report, with
the assistance of Inserm departments. The Centre team, consisting of engineers, researchers
and a secretariat, implements the document searches, logistics and chairing of the expertise
meetings. The team contributes to the scientific writing and to compiling the expertise
products. Regular exchanges with other public organizations (EPST) implementing the same
type of collective expertise have enabled similar procedures to be set up.
Problem statement
The problem statement phase enables definition of the institution's request, checking that
accessible scientific literature on the issue raised is available and drawing up specifications
which state the framework of the expertise (status report on the perimeter and main themes
of the subject), its duration and budget, documented by a convention signed by the sponsor
and Inserm.
During the problem statement phase, Inserm also organizes meetings with patient
associations in order to ascertain the questions those associations wish to have addressed
27
Inserm accredited label
Collective Expert Report
- 207 -
13/12/2011
and the data sources available to them. The information is incorporated in the scientific
program of the expertise. For certain subjects, exchanges with industrial partners are
indispensable in order to obtain access to complementary data not available in the databases.
Expertise monitoring committee and assistance unit setup
A monitoring committee consisting of the institution and Inserm representatives is set up.
The committee meets several times during the expertise to monitor the progress of the
review, discuss any difficulties encountered in addressing the issues, ensure compliance with
the specifications and examine any new factors in the regulatory and political context
pertinent to the ongoing review. The committee also meets at the end of the expertise for
presentation of the conclusions and prior to compilation of the final version of the report.
For expertises addressing sensitive issues, an assistance unit is also set up and consists in
representatives of the Directorate General of Inserm, scientific board, ethical committee of
Inserm, communication department, human and social science researchers and specialists in
the history of science. The role of that unit is to identify, at the start of the expertise, the
issues liable to have strong resonance for the professionals involved and civil society, and to
suggest hearings of professionals in related fields, representatives of civil society and patient
associations. In short, the unit is responsible for measuring the perception that the various
recipients may have of the expertise. Before publication of the expert report, the assistance
unit pays special attention to the wording of the synthesis and recommendations, including,
if necessary, the expression of the various points of view. Downstream of the expertise, the
unit is responsible for strengthening and enhancing the circulation of the results of the
expertise, for instance by holding colloquia or seminars with the professionals of the field
and players involved or holding public debates with representatives of civil society. Those
exchanges are to ensure enhanced understanding and adoption of the knowledge generated
by the expertise.
Literature searching
The specifications drawn up with the institution are translated into an exhaustive list of
scientific questions reflecting the perimeter of the expertise with the assistance of referral
scientists in the field and members of Inserm. The scientific questions enable identification of
the disciplines involved and construction of a key-word arborescence employed in the
systematic searching of international biomedical databases. The articles and documents
selected on the basis of their pertinence with respect to answering the scientific questions
constitute the document base, which is forwarded to the experts. Each member of the group
is asked to add to the document base over the course of the expertise.
Institutional reports (parliamentary, European, international, etc.), raw statistical data,
associations' publications and other documents from the gray literature are also inventoried
(non-exhaustive) in order to complement the academic publications provided to the experts.
The experts are responsible for taking or not taking into account those sources depending on
the interest and the quality of the information supplied. Lastly, a review of the main articles
in the French press is supplied to the experts during the expertise in order to enable them to
follow developments on the theme and the social repercussions.
Collective Expert Report
- 208 -
13/12/2011
Constitution of the expert group
The expert group is formed on the basis of the scientific skills necessary for analysis of the
bibliography collected and on the basis of the complementarity of the group members'
approaches. Since an Inserm collective expertise is defined as a critical analysis of the
academic knowledge available, the choice of the experts is based on their scientific skills
certified by publications in peer-review journals and their recognition by their peers. The
expert recruitment logic, based on scientific skills and not on knowledge in the field, is to be
stressed in that it is a frequent source of misunderstandings when the expert reports are
published.
The experts are selected from the French and international scientific community. They are to
be independent of the partner sponsoring the expertise and recognized pressure groups. The
composition of the expert group is validated by the Directorate General of Inserm.
Several scientists outside of the group may be requested to contribute occasionally to a
particular theme during the expertise.
Expert review implementation lasts between 12 and 18 months, depending on the volume of
literature to be reviewed and analyzed and the complexity of the subject.
Initial expert group meeting
Before the first meeting, the experts receive a document explaining their mission, the
scientific program (issues to be addressed), schedule, the expertise bibliographic database to
date and articles more specifically addressing certain experts on the basis of the skills.
During the first meeting, the expert group discusses the list of issues to be reviewed and
completes or modifies it. The group also examines the document base and proposes
supplementary searches with a view to enriching that base.
Expert critical analysis of the literature
During the meetings, each expert orally presents a critical analysis of the literature with
respect to the aspect allocated to the expert in his/her field of expertise and communicates
the accepted facts, uncertainties and controversies with respect to current knowledge. The
questions, remarks and points of convergence or divergence elicited by the group analysis
are taken into consideration in the section that each of the experts compiles. The analysis
report, consisting of various sections, thus constitutes the state of the art for the various
disciplines pertinent to the issue under review. The bibliographic references used by the
expert are cited in and at the end of each section.
Synthesis and recommendations
The synthesis summarizes the broad lines of the literature analysis and identifies the main
findings and principles. Contributions from contributors outside the group may be
summarized in the synthesis.
The synthesis is more specifically intended for the institution and decision-makers with a
view to use of the knowledge presented therein. The wording of the synthesis is to take into
account the fact that it will be read by non-scientists.
As of report publication, the synthesis is posted on Inserm's website. The synthesis is
translated into English and posted on the NCBI/NLM site (National Center for
Collective Expert Report
- 209 -
13/12/2011
Biotechnology Information of the National Library of Medicine) and Sinapse site (Scientific
INformAtion for Policy Support in Europe, European Commission site).
If requested by the institution, certain collective expertises include 'recommendations'. Two
types of 'recommendations' are formulated by the expert group. 'Principles for action' based
on a validated scientific reference system with a view to defining future public health action
(mainly in screening, prevention and management) but which are not under any
circumstances to be considered 'operational' recommendations insofar as no economic or
political components have been taken into account in the scientific analysis. 'Research
orientations' are also proposed by the expert group with a view to filling in the gaps in
scientific knowledge observed during the analysis. Once again, these proposals cannot be
considered 'priority' research without their being put into perspective. That is the task of the
pertinent authorities.
Critical review of the report and synthesis by prominent 'readers'
For certain expertises addressing sensitive subjects, a critical reading memorandum is
requested from several prominent 'readers' selected on the basis of the scientific or medical
knowledge and managing or evaluating French or European research programs or having
contributed to ministerial working groups. Similarly, the report and synthesis (and
recommendations) may be submitted to figures with good knowledge of the 'field' and able
to grasp the socioeconomic and political issues associated with the knowledge (and
proposals) presented in the expertise.
Presentation of the conclusions of the expertise and debate
A seminar open to the various sectors involved in the subject of the expertise (patient
associations, professional associations, unions, institutions, etc.) enables an initial debate on
the conclusions of the expertise. On the basis of that exchange, the final version of the
synthesis document incorporating the various viewpoints expressed is compiled.
Collective Expert Report
- 210 -
13/12/2011