Daytime veiling glare in automobiles
caused by dashboard reflectance
by
Andreas Dunsäter & Marcus Andersson
Division of Industrial Ergonomics
Department of Management and Engineering
Master thesis LIU-IEI-TEK-A--08/00376--SE
Preface
This thesis work has been performed at the Department of Management and Engineering
(IEI) at Linköping University of Technology, Sweden. The work was commissioned by Saab
Automobile AB at the department of Human Vehicle Integration (HVI). The work started in
October 2007 and was finished in April 2008. We have a lot of people to thank for helping us
to carry out this work in a good way.
First of all we like to thank our examinator and supervisor at the University and our
supervisor at Saab. Thank you Torbjörn Alm, for your help to guide us through this work and
your valuable help with this report. Another big thank you to Claes Edgren for your help and
big enthusiasm about this work. Thank you Bo Magnusson for your help.
We also like to express our gratitude to:
Anne Johansson
Magnus Olsson
Hillevi Hemphälä
Fredrich Claezon
Anette Karltun
IEI, for letting us use the car driving simulator
i
Abstract
Veiling glare has always existed in cars, but during the last years it has been brought up as a
big problem. One reason is that glossier materials are being used in car interior design.
Another reason is that the customers who buy the cars are getting more quality conscious.
They demand to get top quality for the high price that they pay for a car, and veiling glare
problems could be regarded as “low quality”.
Veiling glare is when light hits the car interior and reflects into the windshield, causing
mirror-like images in the windshield (ghost images). This can impair the driving experience
in two ways. It can lower the contrast of the road scene and it may be a cluttering for the
driver.
This work handles daytime veiling glare from dashboard reflectance. The purpose was to
investigate the area and to see if Saab can avoid the problem with veiling glare by using
virtual prototyping (see chapter 3.3.1). This has been done by examining if the light
simulation software Speos can be used to simulate and predict veiling glare, and thereby be
used as a tool for better design.
Key words: Veiling glare, dashboard, windshield, Speos, virtual prototyping.
ii
Sammanfattning
Reflexer från interiören i framrutan har alltid existerat i bilar, men under de senaste åren har
det blivit ett allt större problem. En anledning till det är att den interiöra designen blir mer
och mer avancerad och att glansigare material används. En annan anledning är att
bilkunderna har blivit mer kvalitetsmedvetna och bara accepterar toppkvalité av en så dyr
produkt, och reflexer i framrutan kan uppfattas som låg kvalité.
Problemet med reflektionerna uppstår när ljus träffar interiören i bilen och reflekteras upp i
framrutan. Det gör att förarens körkvalité försämras på två sätt. Dels kan det sänka
kontrasterna i förarens synfält och dels kan det vara en störande faktor.
Det här arbetet har begränsats till att hantera reflektioner i framrutan från instrumentpanelen
under dagtid. Syftet med arbetet var att undersöka om Saab kunde undvika problemen med
reflektionerna genom att använda sig av ”virtual prototyping” (se kapitel 3.3.1). Detta har
gjorts genom att undersöka om den ljussimulerande mjukvaran Speos kan användas för att
förutsäga reflektioner från interiören i framrutan, och kan därmed användas som ett verktyg
för bättre design.
iii
Table of Contents
1. INTRODUCTION ......................................................................................................... 1 1.1 BACKGROUND ................................................................................................................... 1 1.1.1 Saab Automobile AB .............................................................................................. 2 1.1.2 Optis ....................................................................................................................... 2 1.1.3 Problem Statement ................................................................................................ 2 1.2 SCOPE ............................................................................................................................. 2 2. PURPOSE AND RESEARCH QUESTIONS ...................................................................... 3 3. THEORETICAL FRAME OF REFERENCE ........................................................................ 4 3.1 LIGHT .............................................................................................................................. 4 3.1.1 Illuminance ............................................................................................................. 6 3.1.2 Luminance .............................................................................................................. 6 3.1.3 To Measure Luminance and Illuminance ............................................................... 6 Calculating .................................................................................................................................................................... 7 Measuring ..................................................................................................................................................................... 7 Black body absorber ..................................................................................................................................................... 8 Luminance Contrast Ratio ............................................................................................................................................ 9 3.1.4 Contrast .................................................................................................................. 9 3.1.5 Reflection ............................................................................................................. 10 3.1.6 Refraction ............................................................................................................. 12 3.2 THE HUMAN EYE ............................................................................................................. 12 3.2.1 Glare ..................................................................................................................... 13 Discomfort .................................................................................................................................................................. 13 Disability ..................................................................................................................................................................... 13 3.2.2 Adaptation ........................................................................................................... 13 3.2.3 Phototropism ....................................................................................................... 13 3.3 VISUAL REDUCTION WHILE DRIVING .................................................................................... 14 3.3.1 Veiling Glare ......................................................................................................... 15 3.4 METHODOLOGY ............................................................................................................... 17 3.4.1 Simulation‐based design ...................................................................................... 17 3.4.2 Methods for data collection ................................................................................. 17 Method of Adjustment ............................................................................................................................................... 18 Staircase method ........................................................................................................................................................ 18 Double Staircase Method ........................................................................................................................................... 20 Questionnaire ............................................................................................................................................................. 20 Objective measures .................................................................................................................................................... 20 4. 4.1 4.2 4.3 4.4 5. METHOD ................................................................................................................. 21 PROJECT REALIZATION ...................................................................................................... 21 STARTUP ........................................................................................................................ 22 STAIRCASE METHOD ......................................................................................................... 23 QUESTIONNAIRE .............................................................................................................. 23 APPARATUS ............................................................................................................ 24 5.1 SPEOS ............................................................................................................................ 24 5.1.1 Squale ................................................................................................................... 24 BRDF ........................................................................................................................................................................... 25 iv
5.1.2 Ray Tracing........................................................................................................... 25 5.1.3 Photon Mapping .................................................................................................. 25 5.1.4 Viewer .................................................................................................................. 25 5.1.5 CIE ........................................................................................................................ 26 5.2 SMART EYE ..................................................................................................................... 26 5.3 DRIVING SIMULATOR ........................................................................................................ 27 5.4 PHOTOMETER ................................................................................................................. 28 5.5 LIGHT TRAP ..................................................................................................................... 28 6. REALIZATION ........................................................................................................... 29 6.1 DIVIDING THE WINDSHIELD INTO ZONES ............................................................................... 29 6.2 ANALYZE OF SMART EYE DATA ........................................................................................... 30 6.3 SPEOS ............................................................................................................................ 31 6.3.1 Scanning of Materials .......................................................................................... 31 6.3.2 Modifying the CAD‐model .................................................................................... 32 6.3.3 Options in Speos ................................................................................................... 34 6.3.4 Viewer .................................................................................................................. 36 6.3.5 Simulated images with Speos .............................................................................. 37 6.4 DRIVER STUDY ................................................................................................................. 39 6.4.1 Driver Study Procedure ........................................................................................ 39 Preparation for Driver study ....................................................................................................................................... 39 Realization of the Driver Study ................................................................................................................................... 40 6.4.2 6.4.3 7. Indoors ................................................................................................................. 42 Outdoors .............................................................................................................. 43 RESULTS .................................................................................................................. 44 7.1 VALIDATING SPEOS .......................................................................................................... 44 7.1.1 Comparing Luminance Values .............................................................................. 44 7.1.2 Comparing Photorealism ..................................................................................... 46 7.2 DRIVER STUDY ................................................................................................................. 47 7.2.1 Intensity test ........................................................................................................ 47 7.2.2 Position test ......................................................................................................... 48 8. CONCLUSIONS AND FUTURE WORK ........................................................................ 51 9. DISCUSSION ............................................................................................................ 55 9.1 STARTUP ........................................................................................................................ 55 9.2 OPTIS ............................................................................................................................ 55 9.2.1 Validating Speos ................................................................................................... 55 9.2.2 Comparing Luminance Values .............................................................................. 56 9.2.3 Comparing Photorealism ..................................................................................... 56 9.3 DRIVER STUDY ................................................................................................................. 56 9.3.1 Intensity test ........................................................................................................ 56 9.3.2 Position test ......................................................................................................... 57 10. BIBLIOGRAPHY ........................................................................................................ 59 APPENDIX A ...................................................................................................................... 62 APPENDIX B ...................................................................................................................... 68 v
APPENDIX C ...................................................................................................................... 69 APPENDIX D ...................................................................................................................... 70 APPENDIX E ...................................................................................................................... 75 APPENDIX F ...................................................................................................................... 81 APPENDIX G ...................................................................................................................... 83 APPENDIX H ...................................................................................................................... 84 vi
Table of Figures
FIGURE 1‐ ELECTROMAGNETIC SPECTRUM (BRITANNICA, 2008) ........................................................................................... 4 FIGURE 2 – CIE SENSITIVITY STANDARD OF PHOTOPIC AND SCOTOPIC VISION (MODIFIED IMAGE) (WIKIPEDIA, N.D.). ....................... 5 FIGURE 3 – SENSITIVITY DURING PHOTOPIC AND SCOTOPIC VISION (STARBY, 1992).................................................................. 5 FIGURE 4 – RELATIONSHIP BETWEEN LUMINANCE AND ILLUMINANCE (STARBY, 1992) .............................................................. 6 FIGURE 5 – REFLECTION FACTORS (STARBY, 1992) ............................................................................................................ 7 FIGURE 6 – EXAMPLE OF SAME LUMINANCE (STARBY, 1992) ............................................................................................... 8 FIGURE 7 – CONTRAST RELATIONSHIP BETWEEN SURFACES (STARBY, 1992) ........................................................................... 9 FIGURE 8 ‐ DIFFERENT CONTRASTS .................................................................................................................................. 9 FIGURE 9 – RELATIVE CONTRAST SENSITIVITY ACCORDING TO CIE (KELLEY, JONES, & GERMER, 2008) ....................................... 10 FIGURE 10 – EXPERIMENT TO DEFINE DIFFERENT REFLECTIONS (KELLEY, JONES, & GERMER, 2008) .......................................... 11 FIGURE 11 – BRDF EXPERIMENT (KELLEY, JONES, & GERMER, 2008)................................................................................. 11 FIGURE 12 – THREE DIFFERENT REFLECTION COMPONENTS (KELLEY, JONES, & GERMER, 2008) ............................................... 11 FIGURE 13 – REFRACTION (KELLEY, JONES, & GERMER, 2008) .......................................................................................... 12 FIGURE 14 ‐ THE HUMAN EYE (LIGHT: HUMAN EYE, 2007) ............................................................................................... 12 FIGURE 15 ‐ VEILING LUMINANCE DISTRIBUTION (MEFFORD ET AL., 2003) ........................................................................... 14 FIGURE 16 – (LEFT) EXAMPLE OF CONTRAST LOWERING VEILING GLARE. (RIGHT) EXAMPLE OF GHOST IMAGES. ........................... 15 FIGURE 17 ‐ REFLECTANCE DEPENDING ON WINDSHIELD RAKE ANGLE (SCHUMANN & FLANNAGAN, 1997) ................................. 16 FIGURE 18 ‐ STAIRCASE METHOD (CORNSWEET, 1962) .................................................................................................... 19 FIGURE 19 ‐ DOUBLE STAIRCASE METHOD (CORNSWEET, 1962) ........................................................................................ 20 FIGURE 20 ‐ AN OVERVIEW FIGURE OF THE REALIZATION OF THE THESIS WORK ....................................................................... 22 FIGURE 21 – SCREENSHOT FROM SPEOS (OPTIS WORLD, 2008) ........................................................................................ 24 FIGURE 22 ‐ SQUALE TOOL (SQUALE, 2008) .................................................................................................................. 24 FIGURE 23 ‐ EXAMPLES OF CIE SKY MODELS (DAYLIGHTING, 2007) .................................................................................... 26 FIGURE 24 ‐ CAMERA AND IR‐FLASH ILLUMINATORS (TECHNOLOGY, 2008).......................................................................... 27 FIGURE 25 ‐ HOW THE SMART EYE SYSTEM WORKS (TECHNOLOGY, 2008) ........................................................................... 27 FIGURE 26 – HAGNER S3 (PERSSON, PHOTAC, HAGNER, & AB, N.D.) ................................................................................. 28 FIGURE 27 – DEFINED AREA WHICH LIGHT SHOULD BE AVOIDED (STARBY, 1992) ................................................................... 29 FIGURE 28 ‐ THE WINDSHIELD ZONES ............................................................................................................................ 30 FIGURE 29 ‐ THE VIEWING ZONES ON THE DASHBOARD ..................................................................................................... 30 FIGURE 30 ‐ GAZE POINTS FROM ONE OF THE SMART EYE FILES ........................................................................................... 31 FIGURE 31 – MATERIAL LIBRARY IN CATIA ...................................................................................................................... 32 FIGURE 32 – DESIGN LINES IN CATIA ............................................................................................................................. 33 FIGURE 33 – CHROME LIST .......................................................................................................................................... 33 FIGURE 34 – HDR IMAGE ........................................................................................................................................... 35 FIGURE 35 – VIEWER SOFTWARE SHOWING THE PHOTOMETRIC IMAGE OF THE SIMULATION ..................................................... 36 FIGURE 36 ‐ LUMINANCE VALUES FROM FIGURE 36 ......................................................................................................... 36 FIGURE 37 – LIGHT MATERIALS AGAINST A DARK DASHBOARD BACKGROUND ......................................................................... 37 FIGURE 38 – DARK DETAIL AGAINST A LIGHT DASHBOARD BACKGROUND .............................................................................. 38 FIGURE 39 ‐ SIMULATED IMAGE OF DARK LINES ON LIGHT BACKGROUND ............................................................................... 38 FIGURE 40 ‐ LUMINANCE VALUES FROM FIGURE 39 ......................................................................................................... 39 FIGURE 41 – PIECE OF PAPERS THAT WAS USED DURING THE INTENSITY TEST ......................................................................... 40 FIGURE 42 ‐ FIELD OF VISION DURING THE INTENSITY TEST ................................................................................................. 41 FIGURE 43 – FIELD OF VISION DURING THE POSITIONING TEST ............................................................................................ 41 FIGURE 44 – SIMULATOR AT LINKÖPING’S UNIVERSITY WITH THE LAMP MOUNTED ABOVE THE COCKPIT ..................................... 42 FIGURE 45 ‐ COMPARISON BETWEEN OUR MEASUREMENTS AND THE RESULT FROM THE SIMULATIONS IN SPEOS .......................... 44 FIGURE 46 – COMPARISON BETWEEN OUR MEASUREMENTS AND THE RESULT FROM SPEOS ...................................................... 45 FIGURE 47 ‐ (LEFT) SIMULATED IMAGE OF LIGHT MEDIUM SIZED LINES ON DARK BACKGROUND. (RIGHT) PHOTOGRAPH OF THE SAME SCENARIO. ...................................................................................................................................................... 46 FIGURE 48 ‐ (LEFT) SIMULATED IMAGE OF DARK MEDIUM SIZED LINES ON LIGHT BACKGROUND. (RIGHT) PHOTOGRAPH OF THE SAME SCENARIO. ...................................................................................................................................................... 46 FIGURE 49 ‐ RESULTS FROM DRIVER STUDY MADE IN THE CAR DRIVING SIMULATOR ................................................................. 47 FIGURE 50 ‐ RESULTS FROM DRIVER STUDY MADE OUTDOOR IN REAL TRAFFIC ........................................................................ 48 FIGURE 51 – THE DIFFERENT FIELDS IN THE WINDSHIELD .................................................................................................... 49 vii
FIGURE 52 ‐ RESULTS FROM THE SIMULATOR .................................................................................................................. 49 FIGURE 53 – RESULTS FROM THE SIMULATOR COLLECTED IN A TABLE ................................................................................... 49 FIGURE 54 ‐ RESULTS WHEN DRIVING OUTDOORS IN A REAL ENVIRONMENT .......................................................................... 50 FIGURE 55 ‐ RESULTS FROM THE OUTDOOR TEST COLLECTED IN A TABLE ............................................................................... 50 FIGURE 56 – RESULTS COLLECTED FROM THE SMART EYE ................................................................................................... 50 FIGURE 57 – VEILING GLARE IN BOTH MAIN WINDSHIELD AND THE SIDE WINDOW ................................................................... 52 FIGURE 58 – (ABOVE) CHROME LIST AGAINST LIGHT DASHBOARD BACKGROUND, (BELOW) CHROME LIST AGAINST DARK DASHBOARD BACKGROUND ................................................................................................. FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 59 – COMPARING DIFFERENT MATERIALS, VOLVO V70, AUDI A4 AND VOLVO C30 .... FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 60 – LIGHT DETAILS ON A DARK DASHBOARD BACKGROUND, LIGHTENED FROM DIFFERENT DIRECTIONS ... FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 61 – VIEWPORTS FROM SHORT, MEDIUM AND A TALL PERSON ................................ FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 62 – GLOSSY DETAILS ON A BLACK DASHBOARD BACKGROUND, LIGHTENED FROM DIFFERENT DIRECTIONS FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 63 – DIFFERENCE BETWEEN A BLACK AND BEIGE DASHBOARD ................................. FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 64 – CHROME DETAIL TOWARDS A BLACK AND BEIGE DASHBOARD BACKGROUND ........ FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 65 – BLACK DETAIL TOWARDS A BLACK DASHBOARD BACKGROUND AND A BEIGE DETAIL TOWARDS A BEIGE DASHBOARD BACKGROUND ................................................................................................. FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 66 – DARK GLOSSY MATERIAL TOWARDS A MATT DASHBOARD BACKGROUND ............. FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 67 – TWO BLACK AND TWO BEIGE DASHBOARD MATERIALS WITH SMALL DIFFERENCE IN MATT SURFACES FEL! BOKMÄRKET ÄR INTE DEFINIERAT. FIGURE 68 – (ABOVE) LIGHT MATERIALS, LIGHT TEXTILE TOWARDS PLASTIC DASHBOARD BACKGROUND (BELOW) PLASTIC DETAIL TOWARDS TEXTILE DASHBOARD BACKGROUND ...................................................... FEL! BOKMÄRKET ÄR INTE DEFINIERAT. viii
1. Introduction
More and more people are getting aware of the problem called veiling glare while driving,
making the problem a big issue for the car manufacturers. Veiling glare is when the
dashboard, or parts of the dashboard, is reflected into the windshield causing veiling images
(ghost images) that disturbs and impairs the drivers contrast and vision of the road scene.
This phenomenon can be very irritating for the driver and it can also be a safety hazard. Most
people have not thought of it as a problem before, but when someone tells them about it, they
get more aware of the problem.
Veiling glare in cars can be divided into two types of glare and problems. One problem is
light colored dashboards that reflect into the windshield causing “a wall” that the driver has
to look through to see the road scene. This veiling glare reduces all the contrasts of the road
scene, making it harder to detect objects. This can both be disturbing for the driver and also
become a safety hazard. The second kind of problem is contrast differences on the dashboard,
automatically causing contrast differences in the windshield because of veiling glare, called a
ghost image. The details that appear in the windshield can be very irritating for the driver.
This problem could be compared with a cluttered screen in a computer-based environment.
The driver study performed in this project, were focused on the level of acceptance with
ghost images displayed in the windshield.
In this report we are handling the problem with veiling glare and how to predict it, in order to
give a basis for better design.
1.1 Background
The phenomenon called veiling glare have always existed and is hard to completely avoid in
windshields. The question is how it can be reduced so that it disturbs the driver as little as
possible. The problem with veiling glare is growing since the car interior designers are using
more chrome and other shiny materials in the design. The attractive shiny dashboard causes
big problems with veiling glare. This has made pedantic customers use dull dashboard
covers, conceal shiny details with dark tape and black spray light colored parts, to get rid of
veiling glare. But it is not only the meticulous customers that complain. Costumers of today
have higher expectations and quality demands on products that they have spent a lot of
money on. It is also important to deliver the best car when the customer will compare
different manufactures. The competition between the different car manufactures today is
extremely high and it is important that the car has no malfunctions which the customer will
regard as disturbing. To meet these demands and further improve the quality, the car
manufacturers have begun to use simulation-based design and virtual prototyping.
It is possible to perform a study to catch the level of acceptance with veiling glare, which
could be used when a virtual prototype is created in Speos. This way Saab can decide in an
early state in the design process if something should be modified to improve the design.
General Motors and Saab have not yet decided to buy the light simulation software Speos. To
test the usefulness of the software they have used consulting favors from Optis and asked us
to perform a research how useful the software could be for Saab.
1
1.1.1 Saab Automobile AB
This work has been done in cooperation with Saab Automobile AB, Trollhättan. The name
Saab comes from “Svenska Aeroplan Aktiebolaget” which means “Swedish Aircraft
Company”. The company was founded in Trollhättan north of Gothenburg in 1937, where
they started producing military aircraft for the Swedish Air Force. In 1944 they expanded into
civil aviation and in 1947 they started to produce cars. Today the car business part of the
company, Saab Automobile AB, is owned by the world’s largest auto maker General Motors.
A big part of Saab is still kept in Sweden and cars are built in the small town of Trollhättan,
where it all started (Saab USA, 2006).
After more than 4 million produced vehicles, Saab cars are still influenced by aircraft design
features. This can be seen and experienced in the cockpit-like ergonomics, the green
illuminanced instruments and the need-to-know information displays. Another thing that has
lived on from the time as an aircraft company is the great focus on safety (Saab USA, 2006).
1.1.2 Optis
Optis is the creator of the software Speos, which will be used during this project. The
company was founded in France in 1989 and is since then supplying manufacturers with
lighting system design. Optis offers software for light simulation and also engineering
consultancy services. They have more than 1200 costumers, mostly in Europe, USA and Asia
(Company history, 2008).
1.1.3 Problem Statement
The main purpose with this work to determine if the simulation software Speos can be used to
simulate veiling glare in a realistic and correct way, to see if Saab would be able to use it for
their needs. It was also important to access how easy or hard the software is to learn. To be
able to validate the results from Speos, other data such as luminance and contrast ratio was
collected by measuring the ghost images in the same light and weather conditions as
simulated.
To understand the real problem with veiling glare, a driver study was carried. This was done
both in real traffic (outdoor environment) and indoors in a simulated environment. The driver
study investigated the importance of intensity and position of the veiling glare. A main
interest was to come up with a veiling glare intensity level that people think is acceptable.
This was done by letting test subjects drive and give their opinions about different intensity
levels. By doing this, the intensity level could be used as a target value in simulations with
virtual dashboard prototypes.
Another part of the thesis work was to determine if ghost images caused by veiling glare are
more disturbing in specific parts of the windshield.
1.2 Scope
This work has been limited to only investigate the reflection of the dashboard into the
windshield. Thus, we did not investigate reflections in the side windows nor direct glare from
the sun or oncoming head lamps. Finally, we did not go very deep into the effects of veiling
glare or external contrast reduction but focused on the ghost image effects on the windshield,
both in terms of location and intensity.
2
2. Purpose and Research Questions
This thesis work investigated the possibilities to visually analyze the reflections of new
designed dashboards into the windshield, by using virtual prototyping and simulation. This
was done using the Speos software, developed by the French company Optis. The purpose
with this is to avoid disturbing glare which will lower the total driving experience and give
Saab bad will. Another goal was to come up with an acceptance level for veiling glare
intensity and to analyze the importance of its position.
The goal is that Saab can use our results and the Speos software as tools for virtual
prototyping of future dashboards and simulator-based studies of their reflection
characteristics in order to minimize related problems in future products.
The questions that we will try to answer are:
•
•
•
•
•
How can Speos be used by Saab?
Can veiling glare be predicted?
How can veiling glare be measured?
How are people affected by veiling glare?
Can a level of accepted veiling glare be found?
3
3. Theoretical Frame of Reference
This chapter contains the background theory that concerns this thesis work and that has been
studied to be able to understand and answer the research questions. Terms and expressions
are explained to give an understanding for the following chapters. The first two parts in the
chapter are about light and the human eye. After that follows a section that is called “Visual
reduction while driving” which is mostly about the main topic, veiling glare. The last part is
about Optis and their simulator-based design software Speos.
3.1 Light
Electromagnetic radiation may vary in strength and in wavelength. The change of wavelength
is described in the electromagnetic spectrum, figure 1. The visible part of the spectrum is
between the wavelength 480 nm and 770 nm. This part of the spectrum is referred as “light”.
This visible part is bounded between the invisible ultraviolet and infrared regions. (Pedrotti &
Pedrotti, 1996).
Figure 1- Electromagnetic spectrum (Britannica, 2008)
There are different ways to describe the strength of the light. This is categorized into two
different categories: radiometry and photometry. Radiometry is the way to measure
electromagnetic radiation (this can be done on the entire electromagnetic spectrum) while
photometry only applies to the visible portion of the optical spectrum. (Pedrotti & Pedrotti,
1996)
The interesting component in this project is the photometry category of the light
measurement. Photometry takes into consideration the human eye, while radiometry involves
purely physical measurement. The eye responds different on different colors, for example
yellow will seem to be much brighter then blue with the same radiant power during the day.
Photometry is measured according to how the human eye detects it, not how a neutral
detector would measure it. Of course people’s eyes are not identical and will see this
information differently. This is why CIE (international commission on illumination, see
chapter 5.1.5) has created a standard response which is represented in figure 2.
4
The right curve, at the green-yellow peak, shown in figure 2 is the luminous efficiency of the
eye during daylight (photopic vision). When the eye is adapted for night (scotopic vision) the
curve shifts towards the blue peak at 510 nm, represented as the left curve. This effect, when
our sensitivity is changed between day and night, is called Purkinjes effect (Pedrotti &
Pedrotti, 1996), (Starby, 1992).
Figure 2 – CIE sensitivity standard of photopic and scotopic vision (modified image) (Wikipedia, n.d.).
It is not only the wavelength that explains how a person will react on light during night. A
human eye will also be much more sensitive to the intensity during the night-time conditions.
In figure 3 the sensitivity levels is displayed for photopic and scotopic vision. (Starby, 1992)
Scotopic
Photopic
Figure 3 – Sensitivity during photopic and scotopic vision (Starby, 1992)
5
3.1.1 Illuminance
Illuminance is a way to measure the strength of the light in an environment. It is a
photometric method to measure how much a surface is lightened (the intensity of the incident
light, per unit area), see figure 4. The unit for illuminance is lumen per m2 or the SI unit lux
(lx). Lux is latin and means light that emits from a light source (Starby, 1992).
Illuminance was often called brightness, but this lead to confusion and was changed. (Pedrotti
& Pedrotti, 1996).
3.1.2 Luminance
Basically all the things a person can see are luminance. Light cannot be seen until it hits a
surface and reflects towards an eye. Luminance is often described as the reflection or
emission from a flat, matt surface. This is a measurement of the luminous power that hits the
eye when looking at the surface from a particular angle of view. Luminance is the density of
luminous intensity in a given direction. It explains the quantity of light that falls within a
given solid angle and passes through or is emitted from a particular area. The SI unit for
luminance is candela per square meter (cd/m2). (Starby, 1992)
Illuminance
Luminance
Figure 4 – Relationship between luminance and illuminance (Starby, 1992)
Luminance is defined by:
(1)
Where:
Lv is the luminance (cd/m2),
F is the luminous flux or luminous power (lm),
is the angle between the surface normal and the specified direction,
A is the area of the surface (m2), and
is the solid angle (sr).
3.1.3 To Measure Luminance and Illuminance
There are two ways to obtain the luminance and illuminance values, either to calculate it or to
measure it.
6
Calculating
To calculate the luminance of a surface is quite hard. To get a correct result, the surface has
to be completely matt and this kind of material is hard to find (Starby, 1992).
The formula to calculate the luminance is:
ρ ⋅E
L=
cd / m 2
π
(2)
Where E is the illuminance and ρ is the reflection factor. Examples of reflection factors are
presented in figure 5 (Starby, 1992).
Reflection factor
White paper
Light tree
White enamel
Light grey enamel
Dark grey enamel
Concrete
Clean aluminum
0,80
0,45
0,85
0,60
0,15
0,25
0,90
Figure 5 – Reflection factors (Starby, 1992)
The formula to calculate the illuminance is:
φ
E = lux
A
(3)
Where φ is the luminous flux, which defines as the intensity of a source with visible light.
This quantity is measured in terms of the power emitted per unit solid angle from an isotropic
radiator (theoretical point source that radiates equally in all directions in three-dimensional
space).
Measuring
There are two common ways to measure light with a photometer. The first way is to measure
illuminance in the unit lux (lx). There are plenty of different instruments to measure the
illuminance. One instrument to use is the universal instrument that can measure both
luminance and illuminance. Illuminance is measured by placing a small sensor towards the
light that should be measured.
An example when using illuminance would be when the outdoor light is measured and the
value 35000 lx is received on a sunny day with a small amount of clouds. Then when
measuring indoors the value 100 lx is received. When comparing these values the following
result is obtained:
350
(4)
This calculation shows that it is 350 times brighter outdoors than indoors. The human eye
will not notice that it is that much darker indoors because the eye adapts to the situation. The
eye adapts to the dark room and the sensitivity for the light is much higher. This is why it is
7
important to be very careful when comparing indoor and outdoor results. More about
adaption can be read in chapter 3.2.2 (Persson, Photac, Hagner, & AB, n.d.).
A way to compare the outdoor and indoor result is to use the daylight quote. If we divide the
indoor illuminance with the outdoor illuminance; 100/35000=0,00285. The so called daylight
quote is obtained, given in percent. The quote shows how much of the illuminance outdoors
that remains indoors when you made the measurement. It is important to remember that the
daylight quote will change in different places of the room. It is also important to remember
that the clouds might change on the sky which will give different results when measuring
illuminance outdoors (Persson, Photac, Hagner, & AB, n.d.).
To get a value of the luminance, the reflections from a surface is measured with a
photometer. You cannot always trust that what you perceive is the reality. A luminance meter
would get the same value for the grey fields below, but an illusion will make them look
different. The grey color on the lighter background will look darker than on the black
background, see figure 6 (Starby, 1992).
Figure 6 – Example of same luminance (Starby, 1992)
It is wise to document what is measured and in what circumstances. Below some examples
are presented which are important to document when collecting values with a photometer.
•
•
•
•
•
•
•
•
Which visual remarks were noticed?
Why did you take these measurements?
What did you measure? Lighting in a room? Luminance on a display? Daylight in a
landscape?
How did you measure?
Where, for an example in a car, did you do your measurements? This is answered
with words and a simple sketch.
Where there any light recommendations for the situation? How did your values
compare to the given values?
Own thoughts.
Describe with words (and images) if something is uncertain.
By writing these things down it is easy to create knowledge of what is obtained (Persson,
Photac, Hagner, & AB, n.d.).
Black body absorber
The strongest reflection on a windshield occurs when the background is black. This is
because the reflections created on the windshield are brighter. When the background is
brighter the reflections will blend into the background. So when measuring a reflection it has
to be done towards a black background to be able to compare different measured values. The
reason why it has to be completely black is that it will be constant in all different light
8
situations. If a grey surface would be used, the color would change in different light
conditions and it would not be constant. A blackbody is a great absorber. (Pedrotti & Pedrotti,
1996).
Luminance Contrast Ratio
There are often given recommendations for the relationship between the luminance fields in
environments where people work. In an office environment the relation 5:2:1 is used. This
means that the working surface should be five times brighter than the surrounding
environment and the table should be two times brighter than the environment. An example of
this is a bright paper placed on a light colored table, see figure 7. It is often the color of the
object that determines the luminance. The working object should not be too bright either, this
will give a blinding effect. More than three times brighter between two surfaces next to each
other, will blind the user (Starby, 1992).
Figure 7 – Contrast relationship between surfaces (Starby, 1992)
3.1.4 Contrast
Conditions for a person to detect objects are either that the object and the background have
different colors, or that there are contrasts. Contrast means that the surfaces have luminance
differences. A high luminance difference means that the contrast is high and also that it is
easy for a person to detect the object. If an object has a low contrast it might not be detected
at all, or if it has to do with long time work, the low contrast can lead to tiredness or headache
(Nyman & Spångberg, 1996).
Figure 8 - Different contrasts
9
The luminance contrast can be expressed with the formula LC, where LC stands for luminance
contrast, LB for background luminance and LO for object luminance. Observe that the
luminance contrast LC has no unit (Nyman & Spångberg, 1996).
(5)
Dark objects on a light background will give a negative luminance contrast and bright details
against a darker background will result in a positive luminance contrast (Nyman &
Spångberg, 1996).
The eye is sensitive to different contrast ratios. Contrast ratio is another word for luminance
contrast. In figure 9 relative contrast sensitivity is displayed according to CIE. The luminance
is adjusted so that the contrast that is supposed to be seen is just noticeable (Starby, 1992).
Figure 9 – Relative contrast sensitivity according to CIE (Kelley, Jones, & Germer, 2008)
3.1.5 Reflection
Reflection is a common problem today for all kinds of working surfaces. If a user is exposed
for reflections, the person will probably change position to avoid the reflections which will
give bad sitting-positions and body ache.
There are relationships between the amount of light incident on a surface and the light that is
reflected from the lightened surface. See 3.1.3 for an example of this relationship.
There are three different types of reflections: Specular, Haze and Lambertian. If the reflection
looks like a mirror, then it is the Specular reflection. The reflection from a common copying
paper is more diffuse and this type of reflection is called Lambertian. Another example of a
Lambertian reflection could be a wall that is painted with a matt color. Many people think
that so called diffused reflection is the same thing as Lambertian reflection, but a diffuser is a
surface that takes light energy away from Specular direction and distributes it into many other
directions. There is also a third kind of reflection that is a combination of Specular and
Lambertian, which is called Haze reflection. To better understand these different kinds of
reflections a simple experiment can be performed. If a laser beam illuminate a very large
white card in a very dark room the general very soft illumination of the whole card is the
Lambertian reflection. The sharp point in the middle is the Specular reflection and the soft
ball around the Specular reflection is the Haze component. To measure these different
reflections accurately is very hard. This is showed in figure 10. (Kelley, Jones, & Germer,
2008)
10
Figure 10 – Experiment to define different reflections (Kelley, Jones, & Germer, 2008)
One way to measure reflectance is to use the BRDF-method which is explained in section
5.1.1. The result of one of these experiments is displayed in figure 11 (Kelley, Jones, &
Germer, 2008).
Figure 11 – BRDF experiment (Kelley, Jones, & Germer, 2008)
The three different components of reflections could be illustrated as figure 12.
Figure 12 – Three different reflection components (Kelley, Jones, & Germer, 2008)
Example of materials with Specular reflection is gold, silver and polished aluminum. Typical
material examples of Lambertian reflections would be matt paper, textile and snow. Finally
an example of materials with Haze reflections would be semi-glossy paper (Starby, 1992).
11
3.1.6 Refractio
on
Refraction means that
t
the lighht change direction
d
wh
hen it passees materials. The reason is that
the speeed of the ligght is changged. It will slow down
n when it ennters a moree solid mateerial and
will inccrease speedd when enteering a thinnner materiaal, se figuree 13. An example of reefraction
would be
b when lighht passes thhrough a winndshield. (S
Starby, 19922).
Figure 133 – Refraction
n (Kelley, Jon
nes, & Germer, 2008)
3.2 The
T Hum
man Eye
e
The roll of the eyee is to conveert light intoo sensory signals. These signals aare sent to the
t brain
t optic neerve (Light: Human eyee).
for trannslation via the
Light enters
e
the eyye through the transpaarent protecctive corneaa and then passes thro
ough the
variablee hole in thee iris called the pupil, see
s figure 14
4. The funcction of the ppupil is to adjust
a
so
that thee right amouunt of light passes throough the eyee. The lightt then reachhes the flexiible lens
which focuses
f
the light on thee back wall of the eye containing the retina. The retina contains
c
receptorrs called roods and connes which translate
t
thee light enerrgy into eleectrical sign
nals and
send theem to the brrain via the optic nervee (Light: Hu
uman eye, 2007).
2
Figure 14 - The hum
man eye (Ligh
ht: Human eyye, 2007)
fo the eye to distinguiish subtle ddetails. This ability
Visual acuity is deefined as thhe ability for
m
factorss which are:
dependss on four major
•
•
•
•
Size
Time
Luminancee
Contrast
12
The size of an object affects the size of the image on the retina. It is not the physical size of
the object that is important, but the visual angle to the object. This means that a small object
in a close distance will create a large image on the retina and can therefore be seen clearly.
The eye also needs time to adjust for good visual acuity. Just as a camera needs more
exposure time in dim light, so does the eye. When the eye gets enough time to adjust, it can
distinguish objects at very low luminance levels. The two other factors that affect visual
acuity, luminance and contrast, is presented in chapter 3.1.2 and 3.1.4.
3.2.1 Glare
Glare occurs mainly in two ways; too much light (measured with an illuminance indicator)
and if the luminance range is too large. Both are disturbing for the affected person, but only
one impairs the vision (Glare, 2007).
Discomfort
Discomfort glare occurs when the iris has adjusted to a very dark environment and then is
exposed for a much brighter environment. A common example is to come out when the eyes
have adjusted to the indoor luminance levels. The iris will adjust rapidly with a little bit of
discomfort, but with no visual impairment during the adjustment (Glare, 2007).
Disability
In the second kind of glare the eye has adjusted to the average luminance of the whole field
of view. A bright point of light in the view will not affect the average luminance in the room
too much, but the light source directly into the eyes will lead to discomfort and disability to
see. This will make a person turn away or cover the eyes to protect them (Glare, 2007).
3.2.2 Adaptation
The eyes have the capability to adapt to different light situations. To adapt from a dark to a
light environment will happen in a couple of seconds, but when adapting from light to dark
could take up to an hour. A common problem is when entering a tunnel, where the eye has to
adapt from a light environment to a dark environment really fast (Starby, 1992).
3.2.3 Phototropism
Phototropism is the name of a phenomenon where the eye is drawn to light objects. This is
often used in commercials to show specific parts more than others.
This is one reason why reflections could be dangerous and irritating, because often the
reflections will appear as brighter objects in the windshield and the eye will wander to these
light areas (Hemphälä, 2007).
13
3.3 Visual Reduction While Driving
There are a lot of factors that contribute to a reduction of visual quality for the driver.
Common for all of them is that they decrease the visual quality by contributing to a reduction
of all the contrast values in the road scene. This will make it much harder for the driver to
detect different objects while driving (Mefford, Flannagen, & Adachi, 2003).
The most obvious reduction factor is the windshield. Even if the windshield is new and clean,
it will reduce the visual performance for the driver to some degree. The road scene looks
different through the windshield than the way it looks like from outside the car (Mefford et
al., 2003).
Another thing that affects the vision for the driver is dirt and scratches on the inside and
outside of the windshield. These factors will decrease the drivers contrast while driving in
daylight, but they will also strongly reduce visual performance at night driving because of
scattered light from oncoming headlamps (Mefford et al., 2003).
The last and maybe least obvious factor is what is called veiling glare. This phenomenon
occurs when light reflects on the car dashboard into the windshield which creates ghost
images of the dashboard in front of the driver, which strongly reduces contrast of the road
scene (see 3.3.1) (Mefford et al., 2003).
A research study has been made by the transportation research institute at the University of
Michigan, USA by Mefford et al. (2003) to see how much these different factors contribute to
the total veiling luminance. The tests were made in sunny conditions which gave a high but
still common level of veiling glare. The amount of dirt on the windshield was also assumed
as normal. The tests were made using eighteen vehicles with different sizes. The result can be
seen in figure 15.
Figure 15 - Veiling luminance distribution (Mefford et al., 2003)
14
The result shows that dashboard reflectance, in the road scene in this report called veiling
glare, is by far the biggest cause to reduction of contrast for the driver. In second comes the
windshield including scratches.
3.3.1 Veiling Glare
As mentioned earlier the phenomenon when light reflects on the dashboard into the
windshield, creating a reduction in contrast of the objects and the background road scene, is
called veiling glare. This phenomenon will make it harder for the driver to detect different
objects while driving. That is because veiling glare lowers all the contrasts in the road scene.
This is especially evident when a light dashboard reflects into the windshield.
Another type of veiling glare is disturbing reflections in the windshield, which is called ghost
images. This occurs for the exact same reason as contrast reducing veiling glare explained
above. The difference is that the problem is not mainly the reduction in contrast, but the
disturbing effect of the reflection in the windshield. The phenomenon occurs because
luminance differences on the dashboard reflect differently into the windshield. Stronger
contrasts give greater risks for annoyance for the driver, but it also depends on the position of
the reflection. The reflections to the right in figure 16 is often called ghost images.
Figure 16 – (Left) Example of contrast lowering veiling glare. (Right) Example of ghost images.
Veiling glare will always exist, at least as long as cars have windshields. But there are ways
to reduce the amount of veiling glare and to make it as little disturbing as possible.
15
The main two factors that you can manipulate to minimize veiling glare are the dashboard
and the windshields design. The amount of light that reflects into the windshield strongly
depends on the windshield angle. Studies have been made to determine its importance and
this can be seen in figure 17. But the fact is that most of the car manufacturers already are
using windshields with angles less than 60 degrees, so much more cannot be done with this
factor (Schumann & Flannagan, 1997).
Figure 17 - Reflectance depending on windshield rake angle (Schumann & Flannagan, 1997)
Another opportunity is to further adjust the windshield design. When discussing this with our
supervisor at Saab, he told us that the windshield already is a very expensive part of the car
and also hard to manufacture as it is today. It is possible to add a cover on the windshield that
will decrease the reflections. The main reason why this is not an option for Saab is because it
is expensive and does not work very well. This means that the only way we will be able to
affect veiling glare in this work, is to experiment with the dashboard design, including
different materials and design objects and investigating their impact on reflection intensity
and positioning.
The way the reflected images appear for the driver also depends on a fifth factor, which is the
brightness of the background environment. A reflected image against a dark background will
create a very disturbing image that strongly reduces contrast of the road scene for the driver.
A bright background on the other hand, will make the reflected images very vague and
transparent, or the driver might not see it at all. This is a factor that can not be controlled in
real life, so we just have to accept it and focus at the factors we can affect.
The worst possible condition for veiling glare would be a very sunny day when the driver is
driving towards a very dark background. This condition is not very common, because most
often the sun also lit up the surroundings. But one case when it could appear is just before the
driver is entering a tunnel. The reason why this case were chosen was because this is an
extreme case and the idea with this report was to see the lowest level of acceptance a
customer would approve when purchasing a car.
16
3.4 Methodology
There are many psychophysical methods that you can use for research purposes in this area.
We present three of them in this paper. The methods have different advantages and
disadvantages which have to be taken into consideration when making a decision of which
one to choose.
3.4.1 Simulation-based design
The use of simulation as a tool in product design is growing and may be seen as a natural step
after the appearance of CAD-based product models in 3D. The purpose of the simulation step
is to investigate the functionality of the product from different perspectives. A less advanced
simulation step is to visualize the product and thus make it possible to assess the visual
features of the product. The use of Speos, as in our project, is a typical application of
simulation-based design, where a CAD-based model of a dashboard is imported and
supplemented with more design features (like dashboard material), which results in a virtual
prototype possible to study under different conditions.
Speos studies and other “technical” simulations do not need a specific simulator but are
carried out on standard computer platforms. A more specific application is where there is a
need for specific hardware, a simulator, and maybe also possibilities to include an operator.
Typical applications here are found in aviation, where human-in-the-loop simulators have
been used for design purposes since decades in addition to the even more traditional use for
training. Now this trend is also coming up in the automotive area and the expression
Simulator-Based Design (SBD) has been coined (Alm, 2007).
The main benefit of using simulation-based design is its contribution in the form of project
time reduction and product quality enhancement. This statement is especially relevant if
virtual prototyping is included in the process but it is also possible in many cases to include
hardware prototypes in the loop. However, the production time for a hardware prototype is
always longer than for a corresponding virtual prototype and does, according to Alm (2008)
not allow for many design iterations but as a final step in an iterative design process this
could certainly be worthwhile.
As will be demonstrated later in this report we have used a combination of these methods in
our study on windshield veiling glare related to dashboard design.
3.4.2 Methods for data collection
In experimental design studies, where simulations or real world applications are used the
question of what, how and sometimes also when to measure is crucial. Behind this there
always is the basic question why, since the purpose of every measure must be very clear. This
is a fact since data analysis is time consuming and to measure everything to be on the safe
side is nothing to recommend.
There are two basic measurement principles, objective and subjective measures. In the
automotive area, both these alternatives are used and often in combination, so also in our
study. Objective measures are often related to performance at any level (e.g., the entire
system including the driver or for some technical sub-system) but also for other specific
purposes like, for instance, environmental light conditions. Subjective measures, on the other
hand, are based on human assessment (Alm, Simulation-based design, 2008).
17
In the following we review some methods for data collection which have been used or
considered in our project.
Method of Adjustment
This is perhaps the easiest method to determine a threshold value. The idea is to let the
subject control the intensity of the stimuli. That means that some sort of control device has to
be provided. If for example an audio test is held, the subject could control the volume with
the control device, instead of telling the test personal what he or she thinks so that they can
change the volume. This makes the test much easier and faster. There are typically two ways
of doing a sound test. One way is to start with a clear sound and let the subject lower the
volume until he or she does not hear anything anymore. The other way is to start with no
volume and let the subject detect when a sound is noticeable. The two tests should be done a
few times, where the threshold is the average value of the tests. The biggest disadvantage
with this method is that you need to have an easily manipulated control device to control the
intensity. This could be hard in many cases. A corresponding technique could be used for
visual image control with a variation of light intensity (Psychophysical methods, 2008).
Staircase method
The staircase method has both some advantages and a few disadvantages compared to other
commonly used methods. When you perform a test using the staircase method, you start at a
specific intensity level and you ask the subject a question. If you are doing a hearing test, the
question should be: Did you hear the beep? If the subject answers yes, you will lower the
intensity on the next stimulus, and if the answers is no, you will raise the volume (Cornsweet,
1962).
According to Cornsweet (1962) there are four decisions the experimenter has to take. At what
intensity the test should be started, how large the steps should be, when the test should be
stopped and when the series should be modified. Cornsweet suggests some rules about how
this should be done:
•
The test should start at an intensity level that is not too far from where you think the
threshold will end up. The step size should be selected so that the test subject does not
respond the same answer more than maximum four times. As in all psychophysical
methods, this method is most efficient when the stimulus steps are the size of the
differential threshold. That means that the steps should be the smallest step that the
test subject can detect.
18
Figure 18 - Staircase method (Cornsweet, 1962)
•
It is a little bit harder to decide when to stop the test. Typically the curve of the test
will look like the one in Figure 18. There will be big changes in the beginning and
then it will converge towards one value. Of course the test is more reliable with long
series, but that will make it very time consuming. A decision has to be made which
factor that is the most important for the specific test. The easiest method to decide
when to stop the test is to determine the number of stimuli responses in advance.
Another and better way is to determine in advance the number of trials after reaching
the threshold plateau. That is because the number of trials before reaching the plateau
is strongly dependant on the starting intensity.
•
There are cases where the step sizes of the staircase method should vary during the
test. If you for example are testing the visual ability in a dark room, the steps should
be large in the beginning and decrease because of the dark adaption. The same
procedure can be used when starting the test at an intensity level that is much higher
or lower than where the threshold will end up. Large steps can be used until getting
close to the final level and after that, it is better to use small steps.
•
The Staircase method is a very efficient method, because it requires very few stimuli
to reach the threshold value, compared to other methods. Another advantage is that is
quite easy to use, but that is also its biggest disadvantage. Because it is so easy, the
tested subject could figure out how the procedure works, which can have impact on
the test answers. There is another similar method that is not as easy to predict.
19
Double Staircase Method
With the double staircase method you use two curves simultaneously where one of them
starts above and one below the threshold value. By using the two different curves randomly,
it will be very hard for the test subject to understand the system. The advantage is that you
still have a very efficient method and also test answers that are little affected by the biases of
the subject (Cornsweet, 1962).
Figure 19 - Double staircase method (Cornsweet, 1962)
Questionnaire
When performing a study it is often important to let the participants be anonymous. To get a
view of the participants of the study, a questionnaire could be used to receive information
about the test subject.
A questionnaire could also be useful to find out about how the test subjects experienced the
test. It is also a great tool to collect knowledge about the participant’s experiences within the
area which the questionnaire handles.
Objective measures
During this project we have used a Hagner S3 to measure the illuminance of the weather
conditions and the luminance to get a value of the intensity of a ghost image. To do this a
light trap was placed in front of the windshield and the luminance of the ghost picture was
measured with a photometer from the inside of the car.
20
4. Method
The chapter begins to explain the start of the thesis work, its content and how the realization
was planned to be able to solve the problems and answer the research questions. It also
contains the methods that we have used to perform the work.
4.1 Project Realization
This thesis work started in October, 2007. The order of realization was strongly influenced by
the cooperation with the French company Optis. The reason for this was that Saab had bought
consulting favors from Optis that lasted during 2007. That meant that a big part of this work
had to be finished during the year of 2007. There was a license deadline for the Speos
software at the end of the year, and a license deadline for the viewer in the middle of January.
Because of that, there was little time to begin with a proper literature study as is usually done.
To be able to validate the results from Speos, our plan was to take photos and do our own
measurements of veiling glare in a real environment. The logic order would have been to
photograph, do our measurements and then simulate the exact same case with the software.
But the lack of time forced us to do it in the opposite order, with the disadvantage that it was
difficult to do the real world measurements in the same weather conditions as in the
simulation sessions.
A main focus was to come up with a target value, contrast acceptance, for Saab to use for
future dashboard design. A driver study was planned to be done to let a number of drivers
perform a test where they gave their opinions about what intensities of veiling reflections in
the windshield that they could accept. A concern was whether the test should be done outside
in the real traffic, or inside in a laboratory. Another thing that was of interest to be
investigated in the driver study was the importance of position. By doing that it would be
possible to appoint if there are positions in the windshield where reflections would be more
disturbing than on other places of the windshield.
To summarize the plan to perform this work, we first of all wanted to see how easy or hard it
was to learn and use the simulation software Speos. This was of course an important factor
for Saab in the decision whether they would buy the software in the future. Another issue in
interest was to test if Speos simulates the reality in a realistic and correct way. This was done
by comparing the simulated images with photographs of the same case, and also by
comparing the luminance values in Speos with our own measurements.
Saabs hopes is in the future to be able to simulate new designed dashboards made in CAD, to
see what they will look like in reality, i.e. virtual prototyping. By doing so it should also be
possible to control that the levels of reflections from the dashboard to the windshield, did not
exceed their maximum luminance target value. The major benefit here should be that Saab
could detect weaknesses in the design at early states. Therefore, one of our goals was to come
up with a luminance contrast value which drivers experience as acceptable. That was the first
part of the Driver study.
The Driver study also included a position test to validate whether there are areas on the
dashboard where the designers have to be much more restrictive with shiny parts and
materials. There might also be areas where they can place objects without disturbing the
driver.
21
To get a structure of the problem, the project was divided into three parts. An overview of the
project can be seen in figure 20.
START/PROBLEM PROBLEM SOLVING
RESULT/DISCUSSION
INFORMATION Searched information PROBLEM/TASK Received/discussed problem Handled problem Made plan for how to solve problem SPEOS Learned about Speos Prepared for simulations Performed simulations MEASUREMENTS Made own measurements and documentations DRIVER STUDY Studied and learned how to make a driver study Performed pre study Performed driver study in car driving simulator Performed driver study in real traffic ANALYZE Analyzed and compared results Figure 20 - An overview figure of the realization of the thesis work
4.2 Startup
To be able to understand the underlying theory for the phenomenon of veiling glare, the
thesis work started with learning about the topic. Information was searched in books, on the
internet and by talking to experts in the specific areas.
Because of an early deadline with Optis, it was not possible for us to control the order of
realization for the thesis work ourselves. Therefore the first session of reading and learning
about the underlying theory of the thesis work, was quiet short. We quickly had to learn about
basic optics to be able to perform the first part of the thesis work. During the cooperation
with Optis and also afterwards, the theory studies that had been interrupted earlier continued.
A visit to Saab in Trollhättan was done in the beginning of October to meet our supervisor
and to get an introduction to the thesis work. Another important event during that visit was a
meeting with the area sales manager and the sales vice-president from Optis, to get an
agreement about how the cooperation between them and us would work out. Usually you
need to participate in a two week training to be able to use the software by yourself.
22
Therefore they just wanted us to decide what we wanted to have simulated, and then they
would make the simulations for us. That was according to us a bad solution, because a big
part of the thesis work was to experience how difficult the software is to learn. Finally they
were convinced that it was possible for us, with some consulting from them, to perform the
simulations.
4.3 Staircase method
We chose this method because it was a reliable and quick method. The only disadvantage
with the method was that the test subjects could easily understand the scheme of intensity
changes, which could affect the results.
4.4 Questionnaire
A questionnaire was used to collect personal data about the drivers and their experiences of
ghost images. The answers from the questionnaire were then analyzed to see relations
between the drivers and the results. The driver’s answers were also used to find further
interesting topics to investigate.
23
5. Apparatus
This chapter describes the light-simulating software Speos. It also contains other subjects
that have to do with the simulator-based design that is handled in this project.
5.1 Speos
Speos is the name of Optis software that is used for virtual prototyping for lighting systems.
Speos can be used as a standalone software, but is most efficient when it is integrated in the
CAD softwares Catia V5 or OptisWorks. The software can be used in numerous ways. For
example you can visualize what an operator, pilot or driver will perceive. It can be used to
simulate lit or unlit appearance of a lighting system. You can also use it as an analysis tool
for contrast, glare, reflections, visibility and obstruction.
Figure 21 – Screenshot from Speos (Optis World, 2008)
The software is used by companies from all over the world and in many industrial fields.
They have customers in areas such as electronics, automobile, aerospace, defense, the
luminaire industry and traditional optics. (Optis World, 2007)
5.1.1 Squale
Optis uses a tool called the Squale to read different materials and determine how they interact
with light. Squale stands for surface quality extractor. Because Optis virtually want to
simulate what objects look like in reality, they must know exactly how different materials
interact with light. By reading the material in a way called BRDF, they know how the
material reflects, absorbs and transmit light. The information is stored in a file that Speos use
when simulating how the light bounces in the environment.
Figure 22 - Squale tool (Squale, 2008)
24
Squale is a tool that can be brought inside a car and make measurements of the different
materials. It is placed against a material and with a press of a button it will read in the
material in just a few seconds. The tool sends out light from the whole spectrum in different
angles against the material and measures the direction and amount of the reflected light. The
Squale is connected to a computer that stores all the information from the measurement in a
file. This file contains what is called BRDF (Squale, 2008).
BRDF
BRDF is a function that describes what a material looks like for the human eye. It is a way to
describe how light interacts with different materials. The shortening stands for; bidirectional
reflectance diffusion function, and it is about the interaction between light and objects.
(Rauwendaal, 2004).
The BRDF function depends on the direction of the incoming light and the outgoing light. It
also depends on the amount of the incoming and outgoing light. The function describes how
much light the material is reflecting, absorbing and transmitting. Different wavelengths
reflect, absorb and transmit different depending on the physical properties of the material and
the BRDF is therefore also depending on the wavelength and the material properties
(Rauwendaal, 2004).
5.1.2 Ray Tracing
Ray tracing is used in 3D computer graphics to create realistic images, computer games and
movie scenes. The technique can handle complicated optics like reflections and refractions
and therefore creates high quality photorealistic environments and images. The idea is to
mathematically visualize images by following the light beams backwards. That means from
the eye through each pixel of the screen, taking in count the contribution of each light source
in the environment to that pixel. If a light beam happens to intersect with an object in the
scene, the pixel will update and the beam will either recast or die out depending on how many
times it is programmed to bounce (Ray tracing, 2007).
There are different algorithms to mathematically solve the rendering equations, and each way
has its benefits. One of these algorithms is called Photon mapping (Ray tracing, 2007).
5.1.3 Photon Mapping
Packets of light called photons are sent out from the light source instead of tracing the light
from the eye. When a photon hits a target, information about incoming direction, intersection
point and the energy of the photon is saved in what is called a photon map. The outgoing
direction of the photon is decided by the surfaces BRDF (see BRDF under 5.1.1). The
programmer decides when the photon should stop bouncing (Photon mapping, 2007).
5.1.4 Viewer
When analyzing a simulation, Optis offers a viewer program that comes with Speos, where
the simulated images can be opened. The viewer has many possibilities to analyze the image
depending on specific interests. With the viewer it is possible to get luminance values from
each pixel in the image, or with a click on the mouse convert the photo realistic image into a
photometric image.
25
5.1.5 CIE
The different skies that are used in Speos are based on definitions made by CIE. The
commission international de la Eclairage or international commission on illumination is a
non-profit organization founded in France in 1913. They provide information about light,
lighting, color, vision and image handling (Daylighting, 2007).
Figure 23 - Examples of CIE sky models (Daylighting, 2007)
CIE have used mathematical models to describe skies, for example clear, overcast and
uniform. A clear sky has a visible sun which of course gives a luminance distribution that is
much brighter around the sun. An overcast sky is cloudy and the sun is not visible. The
distribution of the luminance is symmetrical around the zenith and the radiation from the sun
makes zenith the brightest spot decreasing towards the horizon. A uniform sky is, as the name
sounds, a sky with a uniform luminance, see figure 23 (Daylighting, 2007).
5.2 Smart Eye
Smart eye is a Swedish company that was founded in 1999. The company develop eye
tracking devices, mostly for the automotive industry. With the smart eye system, the purpose
is to track head movement, eyelids and gazing of the driver (Company, 2008).
The system is used to analyze the driver in different ways. By tracking the head movement
and the eye gazing, you can analyze things like how the driver reads the road scene and how
often and during how long time he looks at the speedometer. This information can be used in
many ways. By being able to track the distance between the eyelids, the system can be used
to warn when the driver is about to fall asleep. The main key to be able to do this in an
effective way, is the computerized analysis of video images (Technology, 2008).
26
Figure 24 - Camera and IR-flash illuminators (Technology, 2008)
The system uses one or two cameras depending on what you want to analyze. The system
mainly uses its own illumination by using a number of IR-flash illuminators. These use a
frequency that interferes as little as possible with the outdoor light. That makes the system
reliable in every environment. A camera tracks a number of facial features and uses a 3D
model of a face for matching the features. In this way the position of the head can measured
with high accuracy. The camera also detects the irises and the pupils which together with the
head position makes it possible to track the gazing. Finally it also tracks the distance between
the eyelids by using a 3D model of the eyeball, see figure 25 (Technology, 2008).
Figure 25 - How the Smart Eye system works (Technology, 2008)
5.3 Driving Simulator
In 1996 the industrial ergonomics division (IAV) started a virtual reality and simulation
laboratory at Linköping University. It was started to support design-oriented research and
educational activities in the area of Human-Machine Interaction (HMI). Today the system is
based on a PC platform and is focused on the vehicle area such as aircraft and ground
transportation. This means that future in-vehicle systems (IVS) can be implemented in the
simulator and validated in a complete environment, that is a complete vehicle system and a
realistic traffic scenario (Simulator, 2007).
The simulator hardware consists of five screens and video projectors for an environment
presentation that give a 200 degree field of view. There are two different cockpits, one Saab
27
9-3, andd one Scannia truck coockpit. A soound system
m gives the driver a reealistic feeliing with
sound from
f
the mootor. The sim
mulator is overviewed
o
from a conttrol room w
where the su
upervisor
can conntrol the sim
mulations. The
T driving simulation software is called ASim
m and is deeveloped
by the company
c
ACE Simulattion. ACE is
i a consultiing companny, active inn many indu
ustries as
automootive, telecom, defense,, media etcetera. The simulator
s
has been widdely used in
n design
and evaaluation off different systems. Examples
E
arre adaptivee cruise coontrol, nigh
ht vision
systemss, lane depparture warrning, blindd spot detection, cockkpit conceppts etc. (Sim
mulator,
2007).
5.4 Photome
P
eter
There are
a plenty of
o tools to measure
m
bothh illuminan
nce and lum
minance, durring this pro
oject we
used a Hagner
H
S3, showed in figure 26. When
W
meassuring illum
minance withh this tool, a sensor
is placeed in the ennvironment where the light will be
b measuredd and the illluminance value is
displayeed in lux.
When measuring
m
luminance with a Haagner S3 th
here is a black
b
spot in the mid
ddle that
represennts a measuuring angle of
o one degrree. Within this angle thhe instrumeent is measu
uring the
luminannce at the giiven surfacee (Persson, Photac, Hag
gner, & AB
B, n.d.).
Figure 26 – Hagner S3 (Persson,
(
Pho
otac, Hagner, & AB, n.d.)
m
l
luminance
with the Hagner
H
S3, the
t value thhat is meassured is an average
When measuring
value within
w
the ciircle. It is thherefore impportant to taake a couplle of values on a surfacce to get
an average value of
o the entire area (Persson, Photac, Hagner, & AB, n.d.).
5.5 Light
L
tra
ap
A light trap is a coonstruction used to creeate a completely blackk surface. T
This is simplly a box
with a hole,
h
covereed with a daark diffuse material on
n the inside. Only a sm
mall amountt of light
will entter the boxx through thhe hole andd the dark diffuse
d
wallls will prevvent the lig
ght from
being reeflected insside the boxx. This makkes the surffaces insidee the box coompletely black.
b
A
light traap is used when meassuring on a transparen
nt surface to
t get a constant back
kground,
which is
i done in thhe driver stuudy in this project.
p
Thee light trap was placedd on the hoo
od of the
car in front
f
of thee driver. Thhe luminancce was meaasured from
m the driverr’s seat thro
ough the
window
w towards thhe light trapp.
28
6. Realization
This chapter presents what have been performed during this thesis work. The realizations are
shown in chronological order, although some work was done simultaneously. The chapter
contains a large part where our work with Speos is explained and illustrated with images.
6.1 Dividing the Windshield into Zones
In the planning of how to perform the position test, an idea came up that it would be practical
to divide the windshield into different zones. In doing so, the test drivers could express their
opinions in terms of in which zone it was most disturbing and least disturbing. It would also
be interesting to see where different parts of the dashboard reflect into the windshield.
Because of the bended form of the windshield, a straight line on the dashboard will result in a
bended line in the windshield. The parts of the dashboard that reflects into the windshield
where drivers look most of the time, or be easily disturbed by reflections, should of course be
very clean from reflective materials.
An investigation was made to see if there already exist defined zones that are used by similar
purposes. If there already exist accepted divisions of the windshield in the car manufacturing
world, there is no reason of defining new ones. But after talking to a few persons at Saab
without any results, we decided to define our own zones.
In the design of a working environment it is common to define an area in the ceiling that
cannot contain any lights because of the reflections that will occur on the desk and disturb the
persons which will use it. This is demonstrated in figure 27. In our case we also defined
analogous areas, but instead of marking the ceiling we marked the dashboard where the
different fields would be placed that is reflected into the windshield.
Figure 27 – Defined area which light should be avoided (Starby, 1992)
To do this, a pattern with straight orthogonal lines was taped, see figure 28. The light colored
tape reflected into the windshield and made a clear image of the pattern for the driver. Nine
photographs were taken from the eye position of the driver. These photographs were
transferred into a computer and merged together into one image. By numbering the tape
intersections in the windshield and doing it the same way on the dashboard, it was easy to see
what part of the dashboard that was reflected in a specific position in the windshield. After
performing a test drive, in real life, it was decided where the main view point of the driver
29
was. Another decision that was made was that the windshield should be divided into twelve
different zones, starting from the primary zone in the middle of the drivers gaze straight
forward. The rest of the left part of the windshield was divided into zones where the driver
looks up, down, right, left and also the remaining corners. The secondary right part was
divided into three horizontal zones, see figure 28.
Figure 28 - The windshield zones
By drawing the zones into the image with the tape and numbers, it was easy to translate the
zone lines in the windshield, to their positions on the dashboard. The result is displayed as the
blue lines in figure 29.
Figure 29 - The viewing zones on the dashboard
6.2 Analyze of Smart Eye Data
When investigating if there are any zones in the windshield that could be used when
performing the position test in the driver study. Saab uses Smart eye in their simulator and it
was obvious that it could be useful for us to use Smart eye in this work. Because it is possible
to determine where in the windshield the driver looks, it is possible to get a distribution of
how much the average driver looks through the different defined zones. That result was then
compared with the result of the distribution from the position test performed in the driver
study. By doing that we could reject or prove the logic idea that the zones that you look
through most of the time, is the areas where you would be most disturbed by reflections
(Claezon, 2008).
30
We got data from an experiment that had been carried out earlier in the car driving simulator
at Saab. The files contained data from tests performed by 14 different drivers, lasting between
nine and forty minutes. The Smart eye saves information about the gaze of the driver
approximately 35 times per second, which made the files quite large. The data was imported
into Excel where some calculations and plots of the gaze points were made. The raw data
could be plotted as a half sphere with the driver’s eye point in the middle. To be able to
compare the smart eye result with our result from the driver study, we had to translate the
coordinates into degrees in x and y. That way the plot was translated from three dimensions
into two, see figure 30. By measuring the angles in a real car from the driver’s eye point, to
the different zones in the windshield, we could determine the placement of the windshield in
the plot (Claezon, 2008).
Figure 30 - Gaze points from one of the smart eye files
The study resulted in 14 tables (see Appendix F) from which a table with mean values was
calculated. That table was then compared with the results from the position test in the driver
study (see 6.4.1).
6.3 Speos
In the following section we describe how the Speos software was used during this project.
This includes descriptions of basic commands and the different options that have to be
entered to get started with the simulations. The CAD-model was already imported into Catia
and was given to us in the beginning of the project. Normally, the CAD-model has to be
created before starting to use Speos.
6.3.1 Scanning of Materials
When simulations are performed in Speos there has to be a material assigned to the object.
Since Speos is integrated to Catia the material library in Catia is used, see figure 31. To
define how the different materials react with light, like reflections and glossiness, the material
is assigned a BRDF file. This is measured with the Squale, which is described in chapter
5.1.1. As mentioned earlier the Squale tool is placed on a desired surface which should be
31
applied on a surface in the simulation. The procedure takes a couple of seconds and is saved
as a BRDF file on the computer which the Squale tool is connected to. One limitation with
the Squale tool is that you cannot measure very shiny materials, for example chrome. Optis
has a material library with different kinds of materials, so in these cases they could send the
desired data to the user.
Figure 31 – Material library in Catia
6.3.2 Modifying the CAD-model
In our case the CAD-model had to be modified, to get a design line in every zone in the
windshield, see figure 32. Different materials was applied on the surfaces in Speos, to see
how the materials react with the light and how ghost images or veiling glare appear in the
window. After deciding that the windshield should be divided into twelve different fields, it
was discussed how to test the materials in these different positions. The decision was to make
these simulations as near the real situation as possible and to create design lines on the
dashboard. Design lines were created as different parts in Catia, so different materials could
be applied individually to each part.
Figure 32 shows the design lines on the dashboard, where the details are marked with orange
lines. Some of the lines had to be divided into two parts, because when creating lines on a
surface in Catia the lines must be created on an intact surface. When starting this project the
geometry was given to us, and the dashboard was divided into different surfaces which made
this a little bit harder.
32
Figure 32 – Design lines in Catia
The lines marked with orange have rectangular shapes with sharp edges, but we also wanted
to test a rounded line, showed in figure 33 marked with orange lines. The reason why this line
was created was to test the effect when a chrome material was applied and to see the shifting
effects with round edges. If chrome was tested on a two dimensional detail the effect would
appear like in a mirror and it would not cast as many reflections. The rounded line was placed
on the right-hand side of the steering wheel because this is a common place for design lines
in cars.
Figure 33 – Chrome list
As soon as all the lines were created on the dashboard it was time to start using the Speos
software and start to create simulations in different light conditions.
33
6.3.3 Options in Speos
Speos is an advanced software including a lot of parameters that must be implemented before
starting the simulations, to get the result the user wants. As mentioned earlier in this rapport
we had deadlines for how long we could use this software and on the 19th of November 2007
we got a two day introduction of how to use the software.
The first day, we were taught how to use the Squale and we measured the different materials
that should be used in the simulations. The software was also installed on one of our own
computers so that we could use the software back in Linköping.
The second day was used to learn how the software worked and how it should be used.
Because of the time limit we only learned the most important things and our tutor prepared
Speos for some simulation cases that we could just manipulate with small changes in the
parameters. The basic values we could change in the software were:
•
•
•
•
•
Light (weather, sun direction, etcetera)
Materials on the dashboard
Height of driver
Resolution of the simulated images
Background of the simulated images
One of the most important issues when creating a simulation in Speos is to define in which
weather conditions the simulation should be performed. In Speos there is a great number of
options to define the weather as exactly as possible. Many of the options are CIE standards
which will make it much easier to declare, described in chapter 5.1.5. The sky has different
definitions which can be chosen. Like clear blue sky, different amounts of clouds on the sky
and finally a sky covered with clouds. It is also possible to define a particular day at a defined
time of the day and the software will calculate how the sun was positioned at that time at this
location. In that case it is important to define the direction of north according to the car.
As mentioned earlier all the details in the CAD design must have a material assigned. This
tells the simulator how the detail responds to light conditions, colors, glossiness and much
more. To read more about the material assignment see chapter 6.3.1.
Different persons are positioned differently in the car, mostly depending on their length. The
result of this can easily be tested in Speos by defining a couple of drivers with different
lengths. The reflections will be experienced differently in the windshield which the
simulation will show by creating an individually image for each driver.
To get a more detailed simulated image it is possible to change the resolution, but when
increasing the resolution the simulation time will increase.
34
To get a realistic view of the simulated image it is important to choose a background that
feels authentic. There are different ways to apply a background. For most of the simulations
performed in this project we created a screen in Catia which was placed in front of the car.
On the screen a photograph was applied with the same background as when we made our
own luminance measurements in the real environment. A photograph was also taken in the
real environment for virtual comparison of the reality and the simulated images in Speos. It is
also possible to create an environment in CAD and simulate this as well. Another option that
we chose to use was to apply a HDR, High dynamic range, image as a background. This is a
360 degree round image that creates a sphere around the object, in our case the car. Another
option was to apply a black background which was used when measuring the luminance
values.
Figure 34 – HDR image
35
6.3.4 Viewer
Figure 35 shows a photometric image simulated in Speos. The line displayed in the
photometric image shows where the luminance measurements have been taken, which can be
seen in figure 36.
Figure 35 – Viewer software showing the photometric image of the simulation
Figure 37 shows the simulation in true color of the photometric image displayed in figure 35.
It is easy to switch between the photorealistic image (figure 37) and the photometric image.
The photorealistic image gives a visual result of the case while the photometric image gives
an overview of the luminance values in the image.
The left top in figure 36 represent the lower line in the windshield, figure 35.
Cd/m2
1
15
29
43
57
71
85
99
113
127
141
155
169
183
197
211
225
239
253
267
281
295
309
323
337
351
365
379
393
40
35
30
25
20
15
10
5
0
Figure 36 - Luminance values from Figure 35
36
6.3.5 Simulated images with Speos
In this section some simulations that were created in Speos will be explained. The
simulations used a background that was photographed from a parking lot at the Linköping
University. The reason why we chose our own background instead of these which were
included in Speos was that we wanted to have the same background in the simulations as in
the real life photographs. Then we could compare the results by just watching the images, to
see if they looked the same or differed.
In the simulations shown in figure 37, the dashboard objects have a light material and the
dashboard background a black material.
Figure 37 – Light materials against a dark dashboard background
37
In the case shown in figure 38 the luminance values will get higher than in the case shown in
figure 37. The black and beige materials used on the dashboard are the same in both these
cases. The reason why the luminance values will get higher in figure 38 than in figure 37, is
that the entire dashboard has a lighter color and the light from outside will bounce against this
light material back and forth between the dashboard and the windshield. In the simulations
mentioned earlier, with a dark dashboard, much more light will be absorbed.
Another thing worth noticeable in this simulated case is that the veiling glare caused by the
light dashboard is very high in the simulated image compared to the reality. An explanation
why a person would not think the veiling glare is as disturbing as the simulated image
(showed in figure 38) is because the eye will adapt to the situation and the person will not
notice that the veiling glare is as disturbing as the simulated image shows. A photometric
image and the diagram of the luminance values is shown in figure 39 and 40.
Figure 38 – Dark detail against a light dashboard background
Figure 39 shows the photometric image of the simulated case, shown in figure 38.
Figure 39 - Simulated image of dark lines on light background
38
The collected data from the photometric image is presented in figure 40.
Cd/m2
1
14
27
40
53
66
79
92
105
118
131
144
157
170
183
196
209
222
235
248
261
274
287
300
313
326
339
352
365
378
391
45
40
35
30
25
20
15
10
5
0
Figure 40 - Luminance values from Figure 39
More simulations can be found in Appendix H.
6.4 Driver study
The driver study was done both in the driving simulator at Linköping’s University and in real
traffic at Saab in Trollhättan. The reason why both locations were chosen was because of the
different advantages. In the indoor environment the light could be controlled and in the
outdoor environment the driver experienced more realistic traffic situations.
6.4.1 Driver Study Procedure
The test was divided into two parts where the first part tested the driver’s level of acceptance
when it comes to intensity of dashboard reflectance into the main viewing field of the
windshield. In the second part, the different positions of the reflections in the windshield
were tested to see how they affected the driver’s opinion of them. In both tests the same
routine was used, which is described in the following section.
Preparation for Driver study
To prepare for the driver studies we used the virtual reality lab at the university to test
different ideas for how the driver study could be done. We also wanted to experience our own
tasks as documentation and changing the intensities, so that it would go as smooth as possible
at the outdoor driver study. The time factor was also important to experience, because we do
not want the test to take too much time for the sake of the tested drivers. When we knew
about how long the test would take, we could also schedule for the driver study and make the
bookings of the drivers.
39
For the intensity test, we used the staircase method to get a threshold for the acceptable
intensity levels of the reflections on the windshield. To vary the intensity of the stimuli we
used 40 mm wide paper strips which we put on the dashboard to reflect into the windshield.
The reflectance of a material depends on the glossiness and the color of the material. We used
30 paper strips with the same glossiness and with colors evenly divided into the gray scale,
see figure 41. We wanted the black strip to be as little reflective as possible so that it would
not reflect into the windshield at all. Therefore we tried to use a paper and a printing
technique which gave a result that was as dull as possible.
Figure 41 – Piece of papers that was used during the intensity test
By using the staircase method, we started at a certain intensity level and let the subject drive a
prepared roundtrip in the city and on the country road. Depending on if the subject thought
the ghost image was disturbing or not, we lowered or raised the intensity level for the next
trial. An important thing that we learned was that the driver only needed a little more than a
minute to make a decision. The staircase method worked very well and we were happy with
the results. The participants of the pre study were also positive.
The second part, which was the position test, did not work out as we had hoped. We used
letters that we placed on the dashboard so that each letter appeared in the different zones of
the windshield. The driver then got to drive for a while to determine and grade how
disturbing the different letters were. The results were very deviant and the grading method
that was used was defective. Therefore we decided to divide the test into eight stages to make
it easier to subject to make a fair decision (Karltun, 2008).
Realization of the Driver Study
The reason for making the study in both an outdoor and indoor environment is that there are
advantages and difficulties with both alternatives. The advantage with making it inside in a
laboratory environment is that the light can be controlled so that all drivers get the exact same
conditions. In an outdoor environment it is impossible to affect the intensity of the light, but
the advantage is that the driver gets to drive in real traffic which gives a higher level of
realism.
The first part of the test we placed a paper strip on the dashboard, see figure 42. The driver
drove a prepared trip for a little more than a minute and answered whether the reflection was
disturbing or acceptable. Depending on the answer we increased or lowered the intensity
level by changing the paper strip, followed by a new trip. After about ten roundtrips we could
determine which maximum intensity level the subject could accept. The contrast between the
40
paper strip and the dashboard background material were measured. In the outdoor test we
also measured the outdoor illuminance level.
Figure 42 - Field of vision during the intensity test
To collect the data, the staircase method was chosen. The double staircase method was not
used because the number of trials would be doubled compared to the staircase method. To
avoid to occupy too much of the test persons time, the staircase method were used. When the
driver had decided the level of acceptance by choosing a paper strip, the luminance was
measured by using the Hagner S3 and the light trap. The light trap was placed on the hood
and the luminance of the ghost picture was measured from the driver’s seat through the
windshield towards the black area of the light trap.
In the second part on the test where we focused on the placement of the reflections, we told
the subjects to drive a different roundtrip, partly to get some change, but also to get a few
more turns so that the driver had to look through different parts of the windshield. In the new
test we used only G:s instead of different letters to make it less messy, see figure 43. The
reason why we used a letter is because it is easier to relate to a letter than a symbol. Twelve
white G:s were placed on the dashboard, with one in each zone. To make it easier for the
subject to grade them, we divided the placement test into eight steps. The first roundtrip they
could only see the top line of G:s, and the second and third roundtrip the middle and low
horizontal lines of G:s. After that the four vertical lines of G:s was visible, and at last all G:s
at once. To hide the G:s that we did not want them to see, we used black patches.
Figure 43 – Field of vision during the positioning test
41
6.4.2 Indoors
After making the pre study, the second part was slightly modified which was important for
the test results. The pre study was also useful for us to learn what to say and what to do, as
preparation for the two real tests.
In the driving simulator we used a lamp that we installed above the car to represent the sun,
see figure 44. We experimented a lot with different lamps to get the right light intensity. A
big problem that we experienced was that it was too dark in the simulator to be able to
measure the luminance in a good way with our luminance meter. When we used a stronger
lamp to brighten up the room, the veiling glare became way too intense because of the
relatively dark background. This case does not happen outside because when the sun is strong
it does not only lighten up the dashboard, it lights up the background environment as well.
You can compare our problem with the case when you are driving towards a dark tunnel on a
very sunny day. The windshield becomes a mirror and you can hardly see anything through
it, which was our case in the driving simulator. Finally we managed to find a lamp that made
it possible to perform the test and measure the luminance.
Figure 44 – Simulator at Linköping’s University with the lamp mounted above the cockpit
Another problem that we had in the simulator was that many of the test subjects suffered
from motion sickness, which in not unusual when driving in car simulators. Unfortunately a
couple of our participants could not complete the test. Otherwise from that both parts of the
test went very smooth.
Another thing that affected the results in the simulator environment was that the test driver
knew that he or she did not drive in a real environment and unconsciously did not pay enough
attention to crossroads, traffic signs etcetera. Some of the test drivers drove the test route
faster and faster and maybe focused too much on the details instead of the environment like
in real life. This was the advantage when driving outdoors. The surroundings distracted the
driver and made him or her concentrate at the details at a reasonable amount of attention.
42
6.4.3 Outdoors
The test was also performed outdoors. The main reason why the driver study was performed
outdoors was that the test persons should drive in a real environment with distractions from
the surrounding and in real sunlight. This was the missing thing in the test performed in the
simulator.
Both the placement and the position test were performed on two different routes that took
about one minute to drive. The driver had to drive in a circulating route because we wanted
the light to shine into the car from all directions. Almost all the drivers commented that they
thought that light from behind was more annoying than when the light was in front of the car.
We chose to perform the tests in an industrial area to keep the risks down, so that no driving
accident should occur. When driving in one direction there was high bushes in front of the car
which made the background very dark even though the sun was strong. This was also
commented by many drivers that they could see the paper strip when driving towards this
dark area. This could be compared with the case when driving towards a tunnel.
The amount of traffic changed randomly during the trials and therefore no pattern could be
discovered as in the simulated environment. The test ran very smoothly with just two persons
that forgot about the test and did not show up.
43
7. Results
The purpose with this work was to investigate the possibilities for car manufacturers to use
Speos to reject or accept virtual dashboard prototypes. To examine the possibilities to do
this, the results from Speos have been compared with our own measurements and
experiments. We have compared the simulated images with photos and also simulated
luminance values compared to our own luminance measurements.
7.1 Validating Speos
All the simulated images in this thesis were done in Speos to test the software and to see if it
is a program that can be useful to Saab. To be able to tell if this is a practical software, the
simulations were compared to a real environment. This was done by measuring the luminance
of the veiling glare against a black surface, using a photo meter. This was done in a similar
weather condition as was used when making the simulations.
It is not only the luminance values that are important in the results when validating this
software. It is also important to see if the simulated images from Speos can be used to get a
visual view of the reality. Because of the time limit these two factors was considered the most
important ones and the focus was directed to these areas.
7.1.1 Comparing Luminance Values
We have validated Speos to see how well the luminance values in the simulated images with
Speos correspond with the luminance values measured in real life.
Cd/m2
45,0
Dark material (our measurement)
40,0
35,0
Dark material (Simulation)
30,0
25,0
Light material (own measurement)
20,0
15,0
Light material (Simulation)
10,0
5,0
0,0
Top Middle Bottom
Figure 45 - Comparison between our measurements and the result
from the simulations in Speos
In figure 45, the luminances from our measurements with a photometer, and the results from
the simulations with Speos are compared. The materials on the dashboard and the weather
conditions were the same. As can be seen, the result is not very different between the two
methods. The measurements and simulation values were taken and collected in the top,
middle and bottom of the windshield. The purpose for this was to show that the luminance of
the veiling glare vary in the windshield.
44
Cd/m2
45,0
Our measurements in real life
40,0
35,0
Dark material
30,0
25,0
Dark material on light background
20,0
15,0
Light material on dark background
10,0
Light material
5,0
0,0
Top
Middle
Bottom
Simulations in Speos
Cd/m2
40,0
35,0
30,0
Dark material
25,0
Dark material on light background
20,0
15,0
Light material on dark background
10,0
Light material
5,0
0,0
Top
Middle
Bottom
Figure 46 – Comparison between our measurements and the result from Speos
As can be seen in the top image in figure 46, we received different values on the same
material, depending on if we measured on a large area or if we measured on a small piece,
lying on a background with a different luminance. When the light hits a larger area, the light
will bounce between the windshield and the dashboard and the interior will get brighter. In
the bottom image that shows the result from the simulations, the two different measurements
of the dark material resulted in the same luminance value. The result is the same in the top,
middle and bottom part of the windshield. The reason for the difference in our measurements
and the result from the simulations will be discussed in the following section.
45
7.1.2 Comparing Phottorealism
m
To be able
a
to anaalyze the usse of the simulations made in Speos
S
by juust looking at them
visuallyy, the imagees was com
mpared withh the photog
graphs takeen of the exxact same case
c
in a
real envvironment. This
T means that the ligght and the materials
m
w the sam
were
me. The factt that the
lines in the windshhield do nott have the saame positio
on, if you coompare the ttwo imagess, should
in this case be iggnored. Thee interestinng thing to observe iss the compparison of intensity
i
betweenn the two images. Thhe result caan be seen
n in figure 47 and 488. The liness in the
windshiield are more distinct in
i the simullated images than in thhe photograpphs. As can
n be seen
if you compare
c
thee simulatedd images wiith the photos, the enviironment inn the backgrround is
darker on the simuulations, whhich will afffect the inttensity of the
t reflectioons and mak
ke them
more visible.
v
The backgrounnd should look
l
exactly
y the samee, to be ablle to make a good
comparrison. The reason
r
for the
t small diifferences between
b
thee images coould be becaause the
backgroound is appplied on a sccreen in froont of the car
c which iss also illum
minated by th
he same
light soource that shhines on the dashboardd. This mak
kes the backkground im
mage darker and the
ghost piictures will be more visible.
Figure 47 - (Left) Simu
ulated image of light mediium sized linees on dark baackground.
(R
Right) Photoggraph of the same scenariio.
ulated image of dark mediium sized linees on light baackground.
Figure 48 - (Left) Simu
(R
Right) Photoggraph of the same scenariio.
46
7.2 Driver study
As mentioned earlier a driver study was performed to get a knowledge of how the customers
assess the reflections in the windshield. The driver study was split into two parts and in this
part of the report the results will be displayed, starting with the intensity of the reflections and
then the placement. When starting and during the driver study each person had to answer
some questions on a questionnaire. This can be found in Appendix A.
7.2.1 Intensity test
The results from the first part of the driver study can be seen in the following images. Figure
49 shows the results from the tests in the driving simulator and figure 50 shows the outcome
of the tests made outside.
As can be seen in the top image in Figure 49 from the simulator tests, most of the test
subjects accepts a contrast level above 0,4. A level of 0,2 was satisfying for all the
participants. The bottom image shows that all test subjects accepted paper strip number 10,
followed by a abrupt change where only a few people accepted paper strip 13. The grey scale
was distributed on 30 paper strips with number one being completely black.
Maximum accepted contrast
2,50
2,00
1,50
1,00
0,50
0,00
Number of subjects that accepted intensity level
1
2
3
4
5 6 7 8 9 10 11 12
Subject number
14
12
10
8
6
4
2
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Grey scale intensity level (Dark to light)
Figure 49 - Results from driver study made in the car driving simulator
This means that most of the test drivers had the same level of acceptance about ghost images
when the light could be controlled in a simulated environment.
47
The top image in figure 50, shows the accepted contrasts in the outdoor test. Most of the test
subjects accept a level around 0,75. There are four fastidious test persons that only accept a
contrast level of 0,1, and two persons that accept a level of 2,5. In the bottom image the
diagram shows that almost all subjects accepted a gray scale intensity level below 6.
Maximum accepted contrast 3,00
2,50
2,00
1,50
1,00
0,50
0,00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Number of subjects that accepted intensity level
Subject number
20
15
10
5
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Grey scale intensity level (Dark to light)
Figure 50 - Results from driver study made outdoor in real traffic
The results from both the indoor and the outdoor tests can be analyzed by comparing the two
top diagrams. Both can be seen as divided into three levels where most of the subjects lie in
the middle field. In both tests there are two persons that accept high veiling glare intensity in
the windshield and there are a few that is very fastidious and hardly do not accept any
reflections at all.
Notice that the indoor and outdoor test ended up at about the same contrast levels. Another
thing to remember is that this is the level of acceptance in the main viewing field of the
windshield. In Appendix C there are some more diagrams that show the different luminance
values of the materials on the dashboard.
7.2.2 Position test
The results from the position test are summed up here in this part of the rapport. The
diagrams show the mean values from the three different tests in the position part of the driver
study. The three different steps of the position test were first to grade the positions in three
steps: horizontal, vertically and to see all the objects on the dashboard. In figure 52 and figure
54 we can see that the lines follow each other and that there is a trend. The results from each
driver are available in Appendix D and E.
48
The vertical axis, of the diagram in figure 52, is the mean value that all the test persons have
used to grade how disturbing the object was in the different fields. The horizontal axis is the
number of the field in the windshield, figure 51.
Figure 51 – The different fields in the windshield
In figure 52 we can see the results from the test in the simulator. As displayed in the diagram,
the users think reflections are most disturbing in the main field that the eye is looking through
when the driver is looking straight forward, the field number six. They also think that it is a
tad more disturbing to the right and less to the left when looking horizontally.
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Figure 52 - Results from the simulator
To sum up the drivers opinions about positions in the simulated environment, the mean
values of all the tests are displayed below. The squares in the figure represent the twelve
different zones in the windshield, as shown in figure 51. The highest percentage means that
this is the zone where the drivers are most disturbed by the reflection.
34,16% 52,62% 37,37% 52,76% 86,90% 55,93% 44,35% 80,57% 54,30% 19,46% 46,43% 35,41% Figure 53 – Results from the simulator collected in a table
49
Figure 54 shows the results from the outdoor test. The upper four fields are much less
disturbing than the other eight. Another thing that can be seen in figure 54 is that there is no
big difference vertically between the zones.
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Figure 54 - Results when driving outdoors in a real environment
The results from figure 54 are summed up in figure 55. The result shows that it is more
important to avoid reflections in the field to the right (number seven), than in the field
straight ahead (number six).
24,67% 61,30% 71,58% 30,83% 78,34% 76,87% 29,52% 79,23% 75,73% 20,26% 67,12% 68,84% Figure 55 - Results from the outdoor test collected in a table
So far we have only looked at the results from Speos and the driver study. In this section we
will see the results from the Smart eye study on in which directions the test drivers looks
through the windshield. It is important to realize that the percent given in figure 55 shows
how the person spends his or her time during a route. This has nothing to do with how
disturbing the different fields are. It is important to remember that the smart eye data has
been collected in a simulated environment. The result shows that the driver looks straight
forward most of the time, followed by looking down and slightly to the right. If that result is
compared with the two results from both the position tests, it can be seen that the same three
zones is the most disturbing zones for a reflection to be present. Another similarity is that the
three least disturbing zones from the outdoor position test (figure 55), correspond to the three
least used zones from the Smart eye result (Claezon, 2008).
1% 7% 6% 3% 40% 18% 1% 12% 5% 1% 3% 4% 5% 63% 32% 14% 61% 18% 8% 100% Figure 56 – Results collected from the Smart eye
50
8. Conclusions and Future Work
In chapter 2 we listed some research questions that we have tried to answer during this thesis.
We have summarized these answers below:
How can Speos be used by Saab?
In chapter 5.3.5 some different cases are displayed for how Speos can be used by Saab. The
software can for example be used to:
• Fast and easy see results without creating mock-ups. This could be reflections in
mirrors or to get values on the light sources.
• Predict veiling glare.
• See how different materials will appear in different light scenarios.
• See how different weather conditions will affect glossiness of materials.
• Visualize the visibility of screen based equipment in different light situations.
• Compare and analyze other car manufactures materials.
Can veiling glare be predicted?
As mentioned earlier, Speos is a great tool for prediction of veiling glare. This is possible
with a fast rendering of the CAD-model directly from Catia. By doing these simulations
during the design process it is easy to find the mistakes that will create veiling glare and this
can be corrected early in the project which saves both time and money.
How can veiling glare be measured?
The easiest way to analyze veiling glare is to calculate the contrast ratio. Of course the
luminance value can be used, but when using the contrast ratio, a difference between the
luminance values will be received, which is a better value on the disturbing factor. Speos is a
great tool to get luminance and contrast values directly in the image.
How are people affected by veiling glare?
As can be seen in our results, most persons that know about veiling glare will think it is
disturbing. Many of the test drivers commented that they would only accept very insignificant
veiling glare in a new car. Some other mentioned that they thought it was more disturbing
when the veiling glare occurred as details in the windshield (ghost images) than the main
veiling glare effect from the entire dashboard. However, as mentioned earlier there are
companies today that sell dashboard covers to put on light dashboards to make it completely
black and matt, so clearly veiling glare is a big problem.
Can a level of accepted veiling glare be found?
As mentioned in the results we can find levels that different persons think would be a level of
acceptance for the contrast ratio. It is important to realize that to make all the customers
satisfied, our results show that there cannot be any contrast differences in the main viewing
field of the windshield.
51
Veiling glare is a big problem for many car manufactures today. When looking at this topic
we found a lot of articles about reflections in displays which will make it harder to see the
information displayed on the screen. During this work we realized that there are interesting
areas to investigate further on. Some of these suggestions were brought up during the driver
study, when the drivers commented on subjects they thought would be interesting to find out
more about. Subjects that we think is interesting for future work are listed.
•
During this project we have realized that when the dashboard is lightened up and
when driving towards something dark, the worst case of veiling glare will occur.
Studies of other conditions and sun positions that cause strong intensity veiling glare
could be interesting in future use of Speos.
•
Because of time limitations, this thesis has only focused of reflections in the main
windshield. By talking to test drivers and testing some different cars, we have found
that reflections in the side windows can be as disturbing as in the windshield in front
of the driver, see figure 57.
Figure 57 – Veiling glare in both main windshield and the side window
•
During the driver study intensity test, the paper strip was placed in the middle field in
front of the driver. This field was chosen because we wanted to get the worst possible
case for the driver. The driver will probably accept higher contrast ratio further away
from the main field. This can be seen in the results from the positioning test. It would
be interesting to further investigate different positions of the details with different
intensity.
•
The angle of the windshield is an important factor for the intensity of the veiling
glare. More research can be done about how the windshield can be manipulated to
reduce veiling glare. It is mentioned earlier in chapter 3.3.1, that veiling glare cannot
52
be further reduced by decreasing the windshield angle to less than 60o, but there may
be other means.
•
During the literature study we found out that elderly people are more sensitive to low
contrast. That means that they need higher contrasts than younger people to be able to
distinguish objects. It would be interesting to look further into this to see how strong
this affects elderly people’s problem with veiling glare. Also, the impact of veiling
glare on contrasts in the driving environment and its implications ought to be studied.
•
Further tests should be done to test the realism of the simulated images in Speos, to
see how they correspond with the real world. This should be done with different
materials imported with the Squale and in different light conditions.
•
The test route outdoors was finished in about one minute and the location was an
industrial road. When performing the driver study in the simulated environment we
found that, when the person was able to drive on both country road and in the city, the
reflections were more annoying in the country road driving. While driving in the city
the driver was focused on cross roads and the entire traffic environment. It might be
interesting to do the outdoor driver study in city traffic, instead of in an industrial
area, to see if the result will be different. It would also be interesting to see if the level
of acceptance would be affected when performing the test on the highway.
When comparing the values from the simulated images and the values that were measured in
the real world, we could see that the values get a little bit too perfect in the simulations. After
discussing this we realized that the values get this perfect because the windshield was too
perfect, with no scratches or dirt. We do not know in this moment if it is possible to add this
factor in Speos, but something we know is that it is possible to change the transparence level
of the windshield.
Other conclusions about the driver study would be that it ran smoothly and we are glad that
we performed a pre study before the real driver study. This taught us how to perform the
driver study as good as possible. We can also see that it was a great idea to perform the driver
study both indoor and outdoor. As mentioned earlier these two different scenarios have their
advantages and therefore it is hard to say which one that is the best. It is easier to measure the
luminance indoors because of the controlled light, but the outdoor test creates more realism
and the drivers will focus on the traffic and drive more accurate. One thing that we could
have done differently in the simulated environment was to use subjects with bigger age
differences.
53
Some positive (pro) and negative (con) aspects concerning the Speos software:
Pro
•
•
•
•
•
Con
•
•
•
Save much money by decreasing the number of mock-ups.
Fast results. The simulations will only take a couple of hours, which is fast compared
to all the time a mock-up will take to build and evaluate.
Possible to create a video sequence to get a more realistic view of the problem.
Integrated with Catia which will make it easier to make design changes and perform
fast simulations after each change.
Possibility to create a design matrix which makes it possible to create many
simulations in one process. That way they can be made at nighttime without any
supervision.
The Squale is bound to a computer and the power net, but a mobile unit will soon be
released.
The license of the software is expensive.
Saab is using Unigraphics as a CAD standard and Speos will only work with Catia
and OptisWorks.
As mentioned earlier, Speos can be used during the early stages of the design process to
predict veiling glare. By using the level of accepted values which has been found during this
project, Saab could easily see if their design is acceptable for their customers. If the veiling
glare has a greater contrast than accepted, they can change the design in an early phase.
We think that Speos is a great virtual prototyping software. Further work must be done and
experience must be achieved to be able to understand and use the software in an effective
way. We believe that Speos could be very useful to Saab in their future work and therefore
we strongly recommend Saab and GM to invest in the software.
54
9. Discussion
The purpose with this work has been to analyze the phenomenon called veiling glare and to
examine if it can be predicted by using virtual prototyping. This was mainly done by
validating the light simulation software Speos.
In this part, the results from the driver study and the simulations are discussed. We also
consider how things could have been done differently.
9.1 Startup
The order of realization of this work was a slightly unusual because of the time limited
cooperation with Optis. The consequence for this was that we did not have much time for
theoretical studies before the Speos activities. This may have had minor implications for
effectiveness in the project but did not affect the end results.
9.2 Optis
Overall the cooperation with Optis worked out well. A very good thing was that we were
allowed to use the software ourselves to make the simulations. By doing this we got a much
greater understanding and knowledge about the software, which we would not have obtained
otherwise. The two tutorial days with the Optis representative, who taught us how to use the
software, was very effective and valuable. After these training days we were able to use the
software almost completely by ourselves, by using templates that David had helped us to
create and with the knowledge we received during the tutorials.
The toughest challenge during the work with Speos was the deadline that forced us to finish
the work with the simulations in the year of 2007. This was a quiet stressful time for us,
where the challenging question was to determine what to simulate. Another problem was that
the software requires a very fast computer to make the simulations. One simulated image
with the 2 Gb RAM computer that we used took almost two hours to complete. Optis offered
their help to use their fast computer to make some of the simulations. Unfortunately, this
cooperation ended up taking much longer time than if we would have done the simulations
ourselves. However, despite these problems we managed to carry out the simulations as
planned.
9.2.1 Validating Speos
The results from the simulations and our measurements are compared in figure 45, were the
luminances in the top, middle and bottom part of the windshield are plotted. There are very
small differences in the two results which indicate that Speos simulates the reality in a
realistic way. One thing that should not be forgotten is that in our values, the luminance from
the windshield has been subtracted. The windshield affects the luminance because of
scratches and dirt (see figure 15), which we have disregarded in figure 45. In the simulations,
we have used a “perfect” windshield with no scratches or dirt which of course is never the
case in the reality. The fact that things tend to be too perfect could be a problem in
simulation-based design and virtual prototyping. This is something that we did not think
about when making the simulations, but it should be easy to change the transparency of the
windshield to make it more realistic. The only problem is to determine how transparent the
windshield should be, which could be an interesting problem to solve in a following thesis
work. First of all, Optis should be contacted to see if they already have a solution for the
problem.
55
9.2.2 Comparing Luminance Values
During this thesis work we had some difficulties measuring veiling glare. The main problems
have been to understand how the luminance meter measures light and how it works. Another
problem has been the light trap which is the black background that we used when measuring
the reflected images. After making some measurements we understood that something was
wrong with our equipment, because we received unreasonable values. After making a new
even darker light trap by using velvet, and learning how the luminance meter really worked,
we received good values.
9.2.3 Comparing Photorealism
In figure 47 and 48 it can be seen that there is a small difference in intensity between the two
images. One reason why the reflections are more distinct in the simulated images depends on
the darker background. The background in the simulations is a photograph taken at the same
time as when the measurements were made. The image is put on a screen in front of the car
geometry, before making the simulation. The simulation made the background slightly darker
because the surface is also lightened by the light source, which made the veiling glare a little
bit more visible.
Because we did not have the possibility to recreate the simulations, we can only speculate if
this is the only reason for the small differences. Further tests should be done to see how well
the simulated images illustrate the reality. This should be done with more materials and in
different light conditions.
9.3 Driver study
The driver study was performed in a simulated environment (indoors) and an outdoors
environment. In an early stage of planning the driver study, we realized that the intensity and
positioning of our reflection are important factors to be able to say how disturbing a
reflection is in the windshield. To test these two parameters it was smartest to split the driver
study into two different parts. That is why we in the following section of the rapport will
discuss the different parts of the driver study individually.
9.3.1 Intensity test
In the first part of the driver study, when we wanted to receive the test subjects opinions
about accepted luminance intensities in the windshield, worked out very well. As described in
3.4.2 about the staircase method, we sometimes started with a light stimulus that was easy to
see in the windshield, and sometimes with a dark paper strip. We could see that it did not
matter on which stimuli the test started, as long as the subject got the opportunity to see both
stimuli far above and below the final threshold.
A great result was that the indoor and the outdoor test ended up at about the same accepted
contrast values. This should of course be the case but there were no guaranty that it would. In
the outdoor test the weather changed and the sun came from different directions, which made
it more difficult for the subjects. Another thing to consider is that the subjects in the indoor
test consisted of much younger people than in the outdoor test (see Appendix G). This could
have affected the test results and it would have been better if we had a wide range of ages in
the indoor test.
The two top diagrams in figure 49 and figure 50 shows the contrast level of acceptance in the
main viewing field. As can be seen there is a pretty big difference in the test subjects opinions
56
of what is acceptable. The fact that people think very different about veiling glare is an
overall image we have experienced during this work. Even though the answers are spread out,
the result is obvious. If Saab want to satisfy also the fastidious customers, it is not acceptable
with any visible reflections at all in the main viewing area. The worst thing is not that these
few customers will dislike the car model, it is the fact that critics will give it bad reputation
which could make it harder to sell the car model.
Figure 45 show that the luminance values in the lower part of the windshield is higher than in
the top part. This is because the distance from the dashboard to the windshield is shorter in
the lower part of the windshield. Our measurements and Speos give the same result.
9.3.2 Position test
We chose to do the positioning test in three different steps as mentioned earlier; horizontally,
vertically and by showing all ghost images at the same time. The reason why it was done this
way was because during the pre study we realized that it was too much information to
compare the details all against each other. The new grouping made it possible for the drivers
to handle less information at the time, which made it easier to grade the zones. Finally when
they had driven the route seven times they should grade all the details at the same time, but
hopefully at this time they had got an idea about what they thought. Some of the test persons
said that they thought it was too much information to handle and others mentioned that they
had an opinion after driving so many times. It is displayed in Appendix B how each test
subject has answered.
It is important to realize that the different points horizontally on a line, in the diagrams, have
no relationship between each other. This kind of diagram should only be a plot diagram
because of no relations, but we chose to draw lines between the plots to easier see a pattern
between the three different parts of this test.
As it is revealed in the results the test persons that performed the test in the simulator think it
is more disturbing to have something in the upper row in the windshield than the persons that
drove outdoors. This is probably because the sky is much darker in the simulated
environment and this result in more visual details. In the outdoor environment the sky is
much brighter and the details will blend into the sky.
It is also noticeable that the drivers are more disturbed by reflections to the right than to the
left. In the simulated environment, the field straight ahead (number six) is the most essential
field, where nothing should be placed to disturb the driver, but in the test outdoors it was
more disturbing to have a reflection in the right field (number seven) next to the field straight
ahead. The reason for the differences in the indoor and outdoor test could be that in the
outdoor environment the driver had to focus more on objects next to the road so that no
traffic accident would occur. If a reflection is placed to the right, it would be harder for the
driver to focus on objects next to the road that might cross the street. Another reason why this
field is more annoying might be when the driver looks straight ahead, he or she will have to
refocus when looking to the right every time. If there is a bright reflection, the eye will
automatically focus on the reflection, because of the phototropism phenomenon.
It is important to realize that the intensity of the details should not be a factor during the
position part of the driver study. This is something that was hard to control, especially during
the outdoor part of the driver study. In the indoor test the intensity of all the stimuli were the
57
same, but in the outdoor test the bright sky made the top stimuli much weaker in intensity. It
was mentioned earlier what consequences this might have had.
Something else that was hard during the outdoor part of the driver study was that the route
contained of a lot of right turns, which might also be a reason for the result that the zone to
the right was the most disturbing. The reason for this was that the car had to return to the
starting position so the driver should drive the same route for every round that the position
parts of the test acquire. We also wanted to have the incoming light from all directions, and at
the same time the route had to be about one minute long. In the simulator it was easy to just
restart the route after performed a trial run. This made it possible to perform both left and
right turns. During the simulator route the driver drove through both city traffic and main
road. This was hard to do in the outdoor environment because of the time limit.
The Smart eye has recorded viewing directions when test persons have been driving. These
data shows how often the driver looks through the different zones in the window. But it is
important to realize that how much the person looks through a field in the windshield, does
not necessarily have to do with what the person will think is more or less disturbing when a
reflection will appear in that field. Of course it is important to see if there is any relation
between these two. As can be seen, the Smart eye result corresponds very well to the driver
study results.
58
10.
Bibliography
Electronic references
Britannica. (2008, January 20). Retrieved January 20, 2008, from Britannica:
http://www.britannica.com/ebi/art/print?id=70892&articleTypeId=0
Claezon, F. (2008, January 10). Internal data. Trollhättan.
Company. (2008, January 18). Retrieved January 18, 2008, from Smart eye:
http://www.smarteye.se/company.aspx
Company history. (2008, January 15). Retrieved January 15, 2008, from Optis-Innovation
ahead of light: http://www.optis-world.com/company/company_history.htm
Daylighting. (2007). Retrieved December 12, 2007, from Square one wiki:
http://squ1.org/wiki/Daylighting
Glare. (2007). Retrieved December 12, 2007, from Square one wiki:
http://squ1.org/wiki/Glare
Kelley, F. E., Jones, R. G., & Germer, A. T. (2008, January 27). The Three Components of
Reflection. Retrieved January 27, 2008, from ftp://ftp.fpdl.nist.gov/pub/reflection/IDDM02ThreeReflectionComponents.pdf
Light: Human eye. (n.d.). Retrieved December 12, 2007, from Square one wiki:
http://squ1.org/wiki/Human_Eye
Light: Human eye. (2007, December 12). Retrieved December 12, 2007, from Square one
wiki: http://squ1.org/wiki/Human_Eye
Mefford, M. L., Flannagen, M. J., & Adachi, G. (2003). Daytime vieling luminance from
windshields: Effects of scattering and reflection. Retrieved October 30, 2007, from Deep
blue: http://deepblue.lib.umich.edu/bitstream/2027.42/55190/1/UMTRI-2003-36.pdf
Optis World. (den 15 November 2007). Hämtat från Optis World: http://www.optisworld.com/speoscaav5/Speos_CAA_V5_1.asp den 15 November 2007
Optis World. (2008, April 19). Retrieved April 19, 2008, from Optis World:
http://www.optis-world.com/speoscaav5/Speos_CAA_V5_LM.asp
Photon mapping. (2007, December 6). Retrieved December 6, 2007, from Wikipedia:
http://en.wikipedia.org/wiki/Photon_mapping
Psychophysical methods. (2008, February 4). Retrieved February 4, 2008, from Optics vision:
http://www.optics-vision.gr/pdf/PSYCHOPHYSICAL%20METHODS.pdF
Rauwendaal, R. (2004). BRDF. Retrieved December 6, 2007, from IDAV-Visualization and
graphics research group: graphics.cs.ucdavis.edu/~bcbudge/ecs298_2004/BRDF.ppt
59
Ray tracing. (2007, December 6). Retrieved December 6, 2007, from Wikipedia:
http://en.wikipedia.org/wiki/Ray_tracing
Saab USA. (2006, February 27). Retrieved March 11, 2008, from News and events:
http://www.saabusa.com/saabjsp/about/pr_060227.jsp
Schumann, J., & Flannagan, M. J. (1997). Science direct, 28 issue 3. Retrieved October 30,
2007, from Science direct: www.sciencedirect.com/science/journal/00224375
Simulator. (2007, October 19). Retrieved March 19, 2008, from Virtual Reality and
Simulation Lab: http://www.iei.liu.se/vrs/sim-oview
Squale. (2008, January 18). Retrieved January 18, 2008, from Optis-Innovation ahead:
http://www.optis-world.com/new_pages/squale/squale.asp
Technology. (2008, January 18). Retrieved January 18, 2008, from Smart eye:
http://www.smarteye.se/technology.aspx
What is light. (2007). Retrieved December 12, 2007, from Square one wiki:
http://squ1.org/wiki/Light
Wikipedia. (n.d.). Retrieved 2 24, 2008, from Wikipedia:
http://en.wikipedia.org/wiki/Luminosity_function
60
Interviews
Hemphälä, H. (2007, December 3). Measuring light. (A. Dunsäter, & M. Andersson,
Interviewers)
Karltun, A. (den 5 February 2008). Statistics. (A. Dunsäter, & M. Andersson, Intervjuare)
Alm, T. (2008, February 25). Simulation-based design. (A. Dunsäter, & M. Andersson,
Interviewers)
Literature
Alm, T. (2007). Simulator-Based Design, methodology and vehicle display applications.
Linköping University.
Cornsweet, T. (1962). The Staircase-Method in Psychophysics. The American Journal of
Psychology (Vol. 75, No. 3). University of Illinois Press.
Nyman, K., & Spångberg, O. (1996). Synen, ögat och arbetet. Futura Statshälsans FoUverksamhet.
Pedrotti, L. F., & Pedrotti, S. L. (1996). Introduction to Optics. New Jersey: Prentice Hall
PTR.
Persson, B., Photac, Hagner, B., & AB, B. H. (n.d.). Hagner-Measures light. Solna: Hagner
AB.
Starby, L. (1992). Belysningshandboken. Stockholm: Ljuskultur.
61
41 – 50 år
51 – 64 år
65 år eller äldre
8. Körvana? Där 5 innebär mycket god körvana.
1
2
3
4
7. Hur ofta kör du bil?
Varje dag
4-6 gånger i veckan
1-3 gånger i veckan
Mindre än 1 gång i veckan
6. Hur länge har du haft körkort:
Mindre än 2 år
2-10 år
Mer än 10 år
5
5. Hur länge har du arbetat på SAAB? ..................... år
3. Längd
160 cm eller kortare
181 – 190 cm
161 – 170 cm
191 – 200 cm
171 – 180 cm
201 cm eller längre
4. Har du någon syndefekt?
Ja: ……………………………………………
Nej
2. Ålder
20 år eller yngre
21 – 30 år
31 – 40 år
......................................................................................................................
......................................................................................................................
......................................................................................................................
Andra kommentarer:
......................................................................................................................
......................................................................................................................
......................................................................................................................
Hur svårt tyckte du det var att bestämma dig för just vilken gråtonsom var
mest irriterande
i detta
test?
......................................................................................................................
......................................................................................................................
......................................................................................................................
Om ja på ovanstående fråga, upplevde du detta som irriterande? På vilket
sätt?
......................................................................................................................
......................................................................................................................
......................................................................................................................
Har du tidigare erfarenhet av reflektioner i bilrutan under körning?
1. Kön
Man
Kvinna
Del 2 - Frågeformulär
Del 1 - Frågeformulär
Appendix A - Driver study questionnaire
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17
Nummer: .......................................................................................................
Del 1 - Intensitetens betydelse
10
2
6
11
7
3
12
8
4
12
11
10
9
8
7
6
5
4
3
2
1
Inte alls
irriterande
Mycket
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2h - Placeringens betydelse
4
8
12
3
7
11
2
6
10
6
7
8
2
3
4
Inte alls
irriterande
5
Mycket
irriterande
10
2
6
11
7
3
12
8
4
Mycket
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2b - Placeringens betydelse
1
Inte alls
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2a - Placeringens betydelse
4
8
12
3
7
11
2
6
10
9
11
12
5
10
Inte alls
irriterande
1
Mycket
irriterande
10
2
6
11
7
3
12
8
4
Mycket
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2d - Placeringens betydelse
9
Inte alls
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2c - Placeringens betydelse
4
8
12
3
7
11
2
6
10
7
11
6
10
Inte alls
irriterande
3
Mycket
irriterande
10
2
6
11
7
3
12
8
4
Mycket
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2f- Placeringens betydelse
2
Inte alls
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2e - Placeringens betydelse
4
8
12
3
7
11
2
6
10
12
8
4
Inte alls
irriterande
Mycket
irriterande
Det här är vindrutan i bilen, som är uppdelad i 12 fält. Placera streck på
skalan nedan för att ange hur irriterande du tycker varje G är.
9
1
5
Del 2g - Placeringens betydelse
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
..................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
...................................................................................................................
Kommentarer: ..........................................................................................
Questionnaire
Appendix B - Answers from Questioner
Do you have earlier experiences of reflections in the windshield while driving?
Yes.
Yes, “Bose”, emblem på Saab 9-3.
No.
Specially when the sun is in front of the car.
Yes, from cars with light dashboards
Yes, for example the strip of chrome in Cadillac BLS
Yes, sometimes when you put your wallet or a paper on the dashboard.
Quite a lot, because I have worked a lot with windshields in Saab 9000.
Yes, at night driving.
Yes, from chrome lists, split lines, loudspeakers.
X7
X2
X2
If yes on the question above, did you experience the reflections as annoying? In what way?
Yes, disturbing reflexes in the viewing field.
X4
Disturbs the concentration.
X3
Sometimes, specially when there is sunshine.
X2
Do not accept high contrasts in the viewing field. Accept reflections along the edges.
X2
Parking tickets when the sun is in front of the car.
Hard to get a clear picture of the surroundings in front of the car
Can be very irritating. Could affect your feeling for distances.
Very irritating, disturbs the total feeling of driving.
Did you think it was hard or easy to determine which reflexes that was annoying and which ones that
was not?
Easy.
X7
Pretty hard.
X3
Pretty hard, depending on the light.
X2
Little different depending on the direction of the incoming light. The ones I experienced as disturbing was
obvious.
Very hard. Many reflections disappeared when you did not focus on them.
Very hard, because of different light conditions, color of the asphalt.
Medium
Other comments
Not the best conditions because of rainy weather
Wonder if it would have been easier in sunlight?
Hard to determine.
Most disturbing with a dark background.
Overall comments
Common with reflections in older cars. More important today to get rid of reflections.
Should also test other conditions as sun, dark and different road surfaces.
Worst case is with the sun behind the car.
More disturbing with G:s vertically than horizontally.
Do not accept reflections from the cars instrument lights.
The side window could also be involved in the test.
Appendix C - Results from Driver
SurveyStudy
Cd/m2
DriverSurveyoutdoor
Study
200
150
100
Darkmaterial
Detail
50
0
1 2 3 4 5 6 7 8 9 1011121314151617181920
Subjectnumber
Lux
50000
45000
40000
35000
30000
25000
20000
15000
10000
5000
0
1 2 3 4 5 6 7 8 9 1011121314151617181920
Subjectnumber
(Top) Difference in luminance between the dark background material and the paper strip.
(Bottom) Light intensity outside when the measurements of the paper strips were made.
Cd/m2
DriverSurveyindoor
Study
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
Darkmaterial
Detail
1
2
3
4
5
6 7 8 9 10 11 12
Subjectnumber
Luminance difference between dark background material and the paper strip.
Appendix D - Testdrivers answers (Simulator)
Person 1
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 2
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 3
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
V ti l
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 4
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 5
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 6
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 7
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 8
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 9
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 10
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 11
100,00%
90,00%
80,00%
70 00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Persom 12
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40 00%
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 13
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
Allll
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 14
100,00%
90,00%
80,00%
70,00%
,
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 15
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Appendix E - Testdrivers answers (Outdoors)
Person 1
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 2
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 3
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
V ti l
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 4
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 5
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 6
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 7
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 8
100,00%
90,00%
80,00%
70 00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 9
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 10
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 11
100,00%
90,00%
80,00%
70 00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Persom 12
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40 00%
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 13
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
Allll
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 14
100,00%
90,00%
80,00%
70,00%
,
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 15
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 16
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
Allll
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 17
100,00%
90,00%
80,00%
70,00%
,
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10 00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Person 18
100 00%
100,00%
90,00%
80,00%
70,00%
60,00%
Horizontal
50,00%
Vertical
40,00%
All
30,00%
20,00%
10,00%
0,00%
1
2
3
4
5
6
7
8
9
10
11
12
Appendix F - Smart-Eye Results
A
B
C
Summa rad
1
2
3
4 Summa kolumn
0,002431 0,002431 0,000663 0,007956
0,013480663
0,049724 0,152265 0,098564 0,041105
0,341657459
0,107182 0,35116 0,087514 0,099006
0,644861878
0,159337 0,505856 0,18674 0,148066
A
B
C
Summa rad
1
2
3
4 Summa kolumn
0,00116 0,005219 0,002609 0,017396
0,026384459
0,032763 0,23688 0,172224 0,057408
0,499275152
0,074804 0,253407 0,092491 0,053639
0,474340389
0,108727 0,495506 0,267324 0,128443
A
B
C
Summa rad
1
2
3
4 Summa kolumn
0,025475 0,053062 0,002904
0,0033
0,084741288
0,100977 0,43783 0,123548 0,040787
0,703141499
0,034055 0,089889 0,044483 0,043691
0,212117212
0,160507 0,580781 0,170935 0,087777
A
B
C
Summa rad
1
0,004547
0,081907
0,046235
0,132689
2
3
4 Summa kolumn
0,020194 0,002711 0,001638
0,029091115
0,441451 0,12512 0,021663
0,670140654
0,162204 0,06143 0,030899
0,300768231
0,623849 0,189262
0,0542
A
B
C
Summa rad
1
0,004668
0,109874
0,161939
0,276481
2
3
4 Summa kolumn
0,001436 0,001436 0,01149
0,019030521
0,190664 0,127469 0,051346
0,47935368
0,177738 0,08833 0,073609
0,501615799
0,369838 0,217235 0,136445
A
B
C
Summa rad
1
2
3
4 Summa kolumn
0,00047 0,028461 0,01964 0,003293
0,051864048
0,050923 0,693285 0,143361 0,014583
0,902152182
0,021051 0,018934 0,002587 0,003411
0,04598377
0,072445 0,74068 0,165589 0,021287
A
B
C
Summa rad
1
2
3
4 Summa kolumn
0,016029 0,011307 0,003106 0,005343
0,035785288
0,139041 0,30256 0,116178 0,045353
0,603131213
0,039389 0,236332 0,053305 0,032058
0,361083499
0,194458 0,550199 0,172589 0,082753
A
B
C
1
2
3
4 Summa kolumn
0,002835 0,010439 0,002449 0,007862
0,023585514
0,096146 0,302101 0,15685 0,044593
0,599690682
0,072303 0,163681 0,090604 0,050135
0,376723805
d
A
B
C
Summa rad
1
0,00458
0,053023
0,023306
0,080908
2
0,077244
0,630267
0,020354
0,727865
3
0,023916
0,130979
0,003969
0,158864
4 Summa kolumn
0,009974
0,115713413
0,016589
0,83085691
0,005801
0,053429676
0,032363
A
B
C
Summa rad
1
0,005138
0,018445
0,050593
0,074177
2
3
4 Summa kolumn
0,015547 0,002899 0,000527
0,024110672
0,443083 0,107905 0,012516
0,581949934
0,287879 0,04585 0,009618
0,393939394
0,746509 0,156653 0,022661
A
B
C
Summa rad
1
2
3
4 Summa kolumn
0,030029 0,068247 0,021552 0,001293
0,12112069
0,079598 0,43477 0,106322 0,026006
0,646695402
0,014799 0,149425 0,039943 0,028017
0,232183908
0,124425 0,652443 0,167816 0,055316
A
B
C
Summa rad
1
0,011211
0,06154
0,024811
0,097562
2
0,038249
0,612357
0,056708
0,707313
3
0,003719
0,103236
0,009827
0,116782
4 Summa kolumn
0,007954
0,061132526
0,039117
0,816249525
0,031272
0,122617949
0,078343
A
B
C
Summa rad
1
0,005567
0,048662
0,015877
0,070106
2
0,025408
0,527057
0,169698
0,722164
3
0,002406
0,123396
0,035259
0,161061
4 Summa kolumn
0,002245
0,035625916
0,020115
0,719231122
0,024308
0,245142962
0,046669
A
B
C
Summa rad
1
0,013465
0,086927
0,094426
0,194818
2
0,009204
0,234873
0,349071
0,593148
3
4 Summa kolumn
0,001704 0,005113
0,029486961
0,081473 0,04227
0,445542867
0,055906 0,025567
0,524970172
0,139083 0,07295
1
0,91%
7,21%
5,58%
13,70%
2
2,62%
40,28%
17,76%
60,66%
3
0,66%
12,26%
5,08%
18,00%
3%
40%
18%
1%
12%
5%
1%
3%
4%
Mean values
A
B
C
Sum row
1%
7%
6%
4 Sum column
0,61%
4,79%
3,38%
63,14%
3,65%
32,07%
7,64%
100,00%
5%
63%
32%
Appendix G - Subject information from Driver
surveyStudy
Men/Women
14
12
10
8
Indoor
6
Outdoor
4
2
0
Men
Women
Age
16
14
12
10
Outdoor
8
Indoor
6
4
2
0
Ͳ20
21Ͳ30
31Ͳ40
41Ͳ50
51Ͳ64
64Ͳ
Length
8
7
6
5
Outdoor
4
Indoor
3
2
1
0
Ͳ160
161Ͳ170
171Ͳ180
181Ͳ190
191Ͳ200
201Ͳ
Appendix H
Confidential information only available in the internal report.
84