TECHNICAL MEMORANDUM- Task C
Task C:
Safety Analysis in Support of Traffic Operations: TxDOT Project 584XXIA001
A SYSTEMIC APPROACH TO PROJECT SELECTION FOR HIGHWAY
WIDENING
DATE:
January 29, 2015
TO:
Darren McDaniel
Texas Department of Transportation
FROM:
Troy Walden, Program Manager
Associate Research Scientist, Texas A&M Transportation Institute
FOR MORE INFORMATION:
Name: Troy Walden, Associate Research Scientist
Phone: 979-845-9943
Email: [email protected]
AUTHORS:
Srinivas Geedipally, Ph.D., P.E.
Myunghoon Ko, Ph.D., P.E.
Lingtao Wu, M.S.
Troy Walden, Ph.D.
Dominique Lord, Ph.D.
A SYSTEMIC APPROACH TO PROJECT SELECTION
FOR HIGHWAY WIDENING
The objective of this report is to present the application of a proposed systemic approach to
project selection for highway widening with a focus on reducing single-vehicle run-off-road
(SVROR) and head-on crashes. The main focus is related to crashes occurring on two-lane rural
highways with a total paved width less than 24ft and traffic volume equal to 400 or more
vehicles per day in the Texas Department of Transportation (TxDOT) roadway network. This
report is divided into two sections. The first section covers the literature review on highway
pavement widening, while the second section presents the analysis results on project selection.
The analytical process of this report is based on the one initially documented in the report titled
Developing Methodology for Identifying, Evaluating, and Prioritizing Systemic Improvements.
1. LITERATURE REVIEW
This chapter summarizes the breadth of the literature pertaining to the relationship between
pavement width and crash risk. The review covers two core topics:

Current design standards and guidelines on pavement width.

Safety effects of widening pavements.
1.1 Introduction
The width of the highway pavement, or typically the width of lanes and paved shoulders, is an
important criterion in the highway design process. Generally, wider lanes and paved shoulders
tend to improve highway capacity and level of service as well as reducing crash risk up to a
certain width. According to a few research studies (Hauer 2000; Bahar et al. 2009; Gross and
Jovanis 2007), very wide pavement width could actually increase crash risk. Furthermore, wider
pavement will significantly increase costs associated with both the construction and maintenance.
Design standards for pavement width (i.e., lane and shoulder widths) are usually dependent on
the roadway functional classification, traffic volume and design speed (Zegeer et al. 1980;
AASHTO 2011; TxDOT 2014a). Local roads, collectors and highways with low volumes can
usually be designed with narrow pavements. However, with the increase in traffic volume and
1
safety concerns, there may be a significant need for widening highways that were already built
with smaller pavement widths. This is also reflected by the large number of current TxDOT
projects that are focused on widening existing roadways (TxDOT 2014b). Before implementing
a pavement widening program, however, it is necessary to better understand the effect of
pavement widths on crash risk. This document therefore summarizes the literature on this topic.
Pavement width plays a different role depending on the classification and category of highways
(Hauer 2000). Previous studies on pavement width have focused on rural two-lane roadways
(Zegeer et al. 1988; Griffin and Mak 1987; Harwood et al. 2000), multilane highways (Lord et al.
2008; Harwood et al. 2003), urban arterials (Potts et al. 2007), and frontage roads (Lord and
Bonneson 2007). For the purpose of this project, the literature review in this report is primarily
directed at rural two-lane undivided highways. The lane width in this report is defined as the
carriageway width on normal segments; widths of other lanes, such as bicycle, pedestrian lanes,
are excluded.
1.2 Design Standards on Pavement Width
Considering the effect of pavement width on safety, highway capacity and level of service
(AASHTO 2011; TRB 2010), design manuals or guidelines specify standards for lane and
shoulder widths.
The American Association of State Highway and Transportation (AASHTO) Green Book in
2011, “A policy on geometric design of highways and streets” (AASHTO 2011), suggests that a
12ft-lane width is desirable on both rural and urban highways. Under some circumstances in
urban areas, a lane width of 11ft or below can be acceptable. According to the Green Book,
under specific characteristics, such as low-speed (less than or equal to 45 mph) and low-volume
(typically, average daily traffic (ADT) under 750 vehicles per day) roads in rural and residential
areas, allow a minimum lane width of 9ft.
The AASHTO Green Book recommends a 10ft-shoulder width along high speed and volume
facilities. A 12ft width is preferable for highways that experience a large number of heavy trucks.
Generally, 6 to 8ft-shoulder widths are preferable, but a 2ft minimum shoulder width can be
considered for low-volume highways.
2
Table 1-1 Width of Lanes and Shoulders on Rural Two-lane Highways (TxDOT 2014a)
Functional Class
Design Speed (mph)
Minimum Width1,2(ft) for future ADT of:
<400
Arterial
Collector
Local6
Lanes (ft.)
All
Shoulders (ft.)
All
Lanes (ft.)
30
35
40
45
50
55
60
65
70
75
80
Shoulders (ft.)
All
Lanes (ft.)
30
35
40
45
50
Shoulders (ft.)
All
400-1500
1500-2000
>2000
43
43 or 83
83
8-103
10
10
10
10
10
10
11
11
11
11
11
10
10
10
10
10
10
11
11
11
12
12
11
11
11
11
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
24,5
45
85
8-105
10
10
10
10
10
10
10
10
10
10
11
11
11
11
11
12
12
12
12
12
2
4
4
8
12
Notes:
1. Minimum surfacing width is 24ft for all on-system state highway routes.
2. On high riprapped fills through reservoirs, a minimum of two 12ft lanes with 8ft shoulders
should be provided for roadway sections. For arterials with 2,000 or more ADT in reservoir
areas, two 12ft lanes with 10ft shoulders should be used.
3. On arterials, shoulders fully surfaced.
4. On collectors, use minimum 4ft shoulder width at locations where roadside barrier is
utilized.
5. For collectors, shoulders fully surfaced for 1,500 or more ADT. Shoulder surfacing not
required but desirable even if partial width for collectors with lower volumes and all local
roads.
6. Applicable only to off-system routes that are not functionally classified at a higher
classification.
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According to TxDOT Roadway Design Manual (RDM) (TxDOT 2014a), the minimum lane
width should be 12ft for high-speed facilities, such as freeways and rural arterials. For low-speed
urban streets, an 11ft- or 12ft-lane width is generally recommended. The minimum lane and
shoulder widths for two-lane rural highways vary according to the average daily traffic (ADT)
and design speed. The specific design criteria can be found in Tables 3-1 (urban streets), 3-5
(suburban roadways), and 3-8 (rural two-lane highways, shown here as Table 1-1) in the RDM
(2014 version).
1.3 Safety Effects of Pavement Width
The conventional wisdom of most engineers is that narrower lane or shoulder will result in more
crashes. The benefit of wider lane(s) and shoulder(s) to safety is usually assumed based on two
reasons: First, wider lanes increase the lateral space between vehicles in adjacent lanes, and
provide a wider buffer to absorb any deviation of vehicles from their intended path. Second,
wider lanes and shoulders provide more room for driver correction in near-collision
circumstances. For example, on a roadway with narrow lane(s) and no paved shoulder, a
moment’s inattention can lead a vehicle over the pavement edge-drop and collision onto roadside
objects, but if the lane(s) are wider and paved shoulder(s) exist, it will provide additional time to
maintain a vehicle on the paved surface. [Example adopted from Bahar et al. (2009) and Hauer
(2000)]. Actually, the conventional wisdom has been demonstrated on rural two-lane highways
(Harwood et al. 2000; Potts et al. 2007).
The safety effect of lane and shoulder widths can be explained by its Crash Modification Factor
(CMF), a multiplicative factor used to compute or modify the expected number of crashes for
highway segments (FHWA 2010). For example, based on a 12ft-lane width, if a particular
roadway section of interest has an 11ft-lane-width, the CMF for the lane width is 1.15. This
implies that a two-lane roadway segment with an 11ft lane would be expected to experience 15
percent more crashes compared to a roadway section with 12ft-lanes (Harwood et al. 2000).
Hauer (2000) conducted a detailed review of literature on lane width (or pavement width) and
safety from published and unpublished documents from the 1950s through 1999. He also
reanalyzed some of the data using improved research methods than those available when the
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original studies were completed (Bahar et al. 2009). Some studies related to this project are
summarized below.
Belmont (1954) examined the crash records on rural two-lane highways in California for the
relationship between shoulder width and crash risk. According to Belmont’s analyses, 6ftshoulders were safer than narrower shoulders, but wider shoulders (>6ft) were observed to
experience more crashes on segments with traffic volumes over 5,000 vehicles per day. Hauer
(2000) reanalyzed Belmont’s data and included pavement width (note that the pavement width
here refers to the total width of the two lanes) in the regression model. CMFs for pavement width
on two-lane highways were further derived from the modeling result, as shown in Table 1-2.
Based on this result, a 22ft-wide pavement on two-lane highways is expected to experience the
lowest number of crashes. When the pavement width is less than 22ft, the expected number of
crashes dramatically increases as the pavement becomes narrower. As the pavement width
increases from 22ft to 26ft, the CMF augments at a relatively slow rate (from 1.0). However,
when the pavement width is greater than 28ft, the expected number of crashes increases quickly.
Table 1-2 CMFs for Pavement Width (Hauer 2000).
Pavement Width (ft.)
18
20
22
CMF
1.21
1.05
1
24
1.01
26
1.06
28
1.13
30
1.21
TTI researchers’ notes:
1. The pavement width in this table means the total width of the two lanes.
2. The result in this table was analyzed based on data collected in the 1950s. Since conditions
such as roadway design standards, vehicles, etc. have changed significantly in the last 60
years or so, it may not be applicable to the current roadway.
Cope (1955) conducted the first before-after study related to pavement widening. The data were
collected based on 22 pavement widening projects, most of which were widening pavements
from 18 to 22ft. Overall, the crash rate (crashes per million vehicle miles traveled) decreased by
about 30 percent after widening the pavement. Hauer (2000) reanalyzed Cope’s data and
considered the Regression-to-Mean (RTM) bias. He concluded that the CMF for widening the
pavement from 18 to 22ft is 0.7. This is equivalent to an 8 percent reduction per foot of lane
widening up to 22ft. Zegeer et al. (1980) studied the effect of lane and shoulder widths on crash
benefits on rural two-lane highways in Kentucky. The main conclusions are: run-off-road (ROR)
and opposite-directions (i.e., head-on) crashes were the only types found to be associated with
5
narrow lanes. Wider shoulders (up to 9ft) were associated with lower crash rates. ROR and headon crashes accounted for 45% and 16% in the data, respectively. Another important finding from
this study is that crash rates for other types of crashes increase as lane width increases. This was
due to faster operating speed on wider lanes.
Griffin and Mak (1987) examined the benefits that could be achieved by widening rural two-lane
farm-to-market (FM) roads in Texas, and concluded that pavement width has no demonstrable
effect on multi-vehicle crash rate. Pavement widening can reduce rates of single-vehicle crashes,
which accounted for about 67% of total crashes (Griffin and Mak 1987; Hauer 2000). This
proportion is consistent with the latest analysis for this type of roads in Texas documented in
Walden et al. (2014).
The Work Codes within TxDOT Highway Safety Improvement Program Manual (TxDOT 2013)
suggests that 30 percent of collisions (same direction sideswipe and head-on) will be reduced
after widening the pavement to maximum 28ft from segments with less than 24ft on two-lane
highways.
Hauer (2000) discussed important highway characteristics associated with pavement width.
Narrower roads are usually designed with lower standards, such as smaller minimum radius and
lower design speed, and also narrower roads tend to carry less traffic. Although this connection
makes the isolated evaluation of pavement width difficult, the overall safety effects of pavement
or lane widths from previous studies (Belmont 1954; Cope 1955; Zegeer et al. 1988) are similar.
Generally, widening pavement width reduces the occurrence of SVROR and head-on crashes.
Harwood et al. (2000) reviewed a broad range of literature (Zegeer et al. 1988; Zegeer et al. 1980;
Zegeer et al. 1994; Miaou 1996; Griffin and Mak 1987) and summarized the CMFs for lane and
shoulder widths on rural two-lane highways, individually. The CMFs for lane and shoulder
widths on rural two-lane highways were then adopted by the Federal Highway Administration
(FHWA) Interactive Highway Safety Design Model (IHSDM) (FHWA 2013) and AASHTO
Highway Safety Manual (HSM) (AASHTO 2010). They are now widely accepted in highway
safety planning, managements, and crash prediction.
6
Gross and Jovanis (2007) applied a case-control design to identify CMFs for lane and shoulder
widths on rural two-lane undivided highways. The result is generally consistent with the CMFs
in the HSM. A “U-shaped” trend was observed for the CMF for lane widths, indicating that very
wide lanes tend to increase crash risk. The data was then reanalyzed using cross-sectional
method, which produced similar results (Gross and Donnell 2011).
Potts et al. (2007) evaluated the relationship between lane width and safety for urban and
suburban arterials. Despite the fact that the analysis was not based on rural two-lane highways, it
was concluded that there was no indication of an increase in crash frequencies as lane width
decreased for arterial roadway segments. This result is opposite to conventional wisdom and
previous work documented above.
For the relationship between pavement width and safety, study results based on different data
sources tend to be inconsistent. For example, according to Hauer (2000), pavement width (total
width of the lanes on rural two-lane highways) shows a “U-shaped” relationship with safety.
Twenty or 22ft-pavement has the lowest crash risk. However, based on the CMFs in HSM, lane
and shoulder widths have monotonic relationships with safety. When the lane and shoulder
widths are within a certain range, the wider they are, the lower the crash risk is. To date, no
consensus has been reached on the CMF for pavement width on rural two-lane highways (note
that the CMFs in HSM are presented for lane width and shoulder width separately; no CMF for
pavement width is available in HSM). One possible reason is more studies were conducted on the
safety effect of lane and shoulder widths, individually. Another possible reason is that the same
pavement width with different lane and shoulder combinations can influence safety differently.
For example, for a fixed pavement width of 24ft, a configuration of two 12ft-lanes with no
shoulder can affect crash risks differently than a configuration of two 11ft-lanes with two 1ftshoulders. Gross et al. (2009) evaluated the safety effectiveness of various lane-shoulder width
configurations for fixed total paved widths as a countermeasure for roadway departure crashes.
In general, wider pavement widths are associated with fewer crashes than narrower paved widths.
Based on the estimated safety effectiveness in this study, specific lane-shoulder configurations
have the potential to reduce crashes on rural two-lane undivided roads differently.
7
1.4 Summary
In sum, the literature review has shown that lane and shoulder widths vary according to the
roadway function, traffic volume and design speed. Generally, higher traffic volume and design
speed require wider lanes and shoulders. In the literature review focusing on the safety effects of
widening pavement width, there is an evidence of the benefits of widening pavement on rural
two-lane highways. Widening pavement width reduces the occurrence of SVROR and oppositedirection crashes. However, some studies have pointed out that very wide lanes or shoulders
might increase crash risk. Although no consensus has been reached on the CMF for pavement
width, there are several CMFs for lane and shoulder widths available from the HSM and other
related literature. TTI researchers recommend using the CMFs in HSM for the analysis in this
study.
2. APPLICATION OF SYSTEMIC APPROACHES ON PROJECT
SELECTION FOR HIGHWAY PAVEMENT WIDENING
This section describes the application of the systemic approach for highway pavement widening.
The section is divided into three parts and covers the target crash type and facilities, risk factors
and risk assessment, respectively. As discussed above, the analysis is based on the procedure
documented in a previously published report.
2.1 Target Crash Type and Facility
According to the TxDOT Crash Records Information System (CRIS), there were 8,439 singlevehicle KA crashes from 2009 to 2013 (see Figure 2-1). ROR crashes are the predominant crash
type, especially in rural areas. Most of SVROR crashes collided with fixed objects, such as trees
or a fence, or overturned after leaving the roadway. More importantly, a little higher than 30% of
SVROR KA crashes occurred on two-lane rural highways with a total pavement width of less
than 24ft. Figure 2-1 shows a crash tree of single-vehicle KA (Fatal and Injury Type A or
Incapacitated) crashes identifying target crash types and facilities.
8
Fatal - 2167 (26%)
Incap. injury- 6272 (74%)
Single Vehicle
8439
On Roadway
1651 (20%)
Overturned
2485 (37%)
Fixed Object
4138 (61%)
ROR
6788 (80%)
Other/Unknown
165 (2%)
Tree, Shrub, Landscaping - 1090 (26%)
Fence - 642 (16%)
Culvert-Headwall - 620 (15%)
Guardrail - 302 (7%)
Embankment- 260 (6%)
Ditch- 259 (6%)
Highway Sign - 224 (5%)
Other Fixed Object - 193 (4%)
Utility Pole - 150 (4%)
Mailbox - 148 (4%)
Others - 250 (6%)
Fatal and Incapacitating Injury Crashes Only
Two-lane Two-way Highways
Source: TxDOT CRIS, 2009-2013
Urban
758 (11%)
Minor Arterial - 342 (45%)
Collector - 215 (28%)
Principal Arterial - 196 (26%)
Others - 5 (1%)
Major Collector - 3327 (55%)
Minor arterials - 1386 (23%)
Minor Collector - 751 (12%)
Principal Arterial - 557 (9%)
Local - 9 (1%)
Rural
6030 (89%)
Total Paved Width
18-20: 1187 (20%)
21-22: 487 (8%)
23-24: 927 (15%)
25-26: 313 (5%)
27-28: 483 (8%)
29-30: 304 (5%)
31-40: 1142 (19%)
>40: 1187 (20%)
ADT
0-399: 768 (13%)
400-999: 1277 (21%)
1000-1999: 1432 (24%)
2000-2999: 887 (15%)
3000-3999: 554 (9%)
4000-4999: 356 (6%)
5000-5999: 250 (4%)
6000-6999: 182 (3%)
7000-7999: 99 (2%)
8000-8999: 79 (1%)
9000-9999: 46 (1%)
>=10000: 100 (2%)
Figure 2-1 Single Vehicle Crash Tree Diagram to Identify Target Crash Types and
Facilities.
Based upon the TxDOT CRIS data, there were fewer head-on crashes than SVROR from 2009 to
2013 (see Figure 2-2). However, head-on collisions resulted in more fatal injuries compared to
SVROR crashes, as expected. Fatal crashes due to a head-on collision accounted for a half of
total head-on KA crashes, while less than one third for SVROR fatal crashes (compared to
SVROR KA crashes). Most head-on collisions occurred in rural areas.
9
Fatal - 1015 (50%)
Incap. injury- 1008 (50%)
Fatal and Incapacitating Injury Crashes Only
Two-lane Two-way Highways
Source: TxDOT CRIS, 2009-2013
Head-on
2023
Urban
358 (18%)
Minor Arterial - 160 (45%)
Principal Arterial - 120 (34%)
Collector - 69 (19%)
Others - 9 (2%)
Major Collector - 633 (38%)
Minor arterials - 584 (35%)
Principal Arterial - 376 (23%)
Minor Collector - 72 (4%)
Rural
1665 (82%)
Total Paved Width
18-20: 139 (8%)
21-22: 85 (5%)
23-24: 151 (9%)
25-26: 43 (3%)
27-28: 121 (7%)
29-30: 66 (4%)
31-40: 413 (25%)
>40: 647 (39%)
ADT
0-399: 37 (2%)
400-999: 113 (7%)
1000-1999: 253 (15%)
2000-2999: 282 (17%)
3000-3999: 229 (14%)
4000-4999: 199 (12%)
5000-5999: 152 (9%)
6000-6999: 141 (8%)
7000-7999: 80 (5%)
8000-8999: 62 (4%)
9000-9999: 31 (2%)
>=10000: 86 (5%)
Figure 2-2 Crash Tree Diagram to Identify Target Crash Types and Facilities.
2.2 Risk Factors
This section describes the risk factors for SVROR and head-on collisions. In order to identify
these factors, TTI researchers collected KA crashes using TxDOT CRIS that occurred for the
2009-2013 time period. The crashes were then categorized by crash types—SVROR and head-on.
SVROR and head-on crashes on two-lane rural highway with a total pavement width of less than
24ft were categorized by variables, such as lane and shoulder widths, ADT, truck presence, and
alignment.
2.2.1 Risk Factors for SVROR
To identify risk factors associated with SVROR crashes, TTI researchers compared the
proportion of KA crashes for a specific range or value of a variable with the proportion of
existing highway mileage within the respective range or value. To remove the biased selection of
higher-volume roads, the ADT variable is divided into three groups: low-volume (400-700 ADT),
moderate-volume (701 to 1,500 ADT), and high-volume (>1,500 ADT). The categorization was
based on approximately equal mileage in each group.
10
Figures 2-3 to 2-5 show the proportions of SVROR KA crashes by different variables (lane and
shoulder pavement width, truck presence, and alignment) for traffic volume groups. For lowvolume group, SVROR crashes are over-represented on two-lane rural highways with 1) a 11ftlane width without paved shoulder, 2) 9 to 15% truck presences, and 3) less than 1,000ft-curve
radius, respectively. For example, on two-lane rural highways with 9 to 15% truck presence,
SVROR crashes account for about 40% of total SVROR KA crashes, while they constitute 34%
of total highway mileage. SVROR KA crashes are over-represented by 6% (the difference
between 40% and 34%). For two-lane rural highways with low-volume, an 11ft-lane width
without paved shoulder, 9 to 15% truck presence, and less than 1,000ft-curve radius are risk
factors for SVROR KA crashes.
For the moderate-volume group, SVROR KA crashes are over-represented on two-lane rural
highways with less than or equal to 8% truck presence and curves (see Figure 2-4(b)). In addition,
crashes are slightly over-represented on highways with a 10ft-lane width or less without paved
shoulders as well as a 10ft-lane and a 1-foot paved shoulder width. As a result, less than or equal
to 8% truck presence, a 10ft-lane width or less with paved shoulders of less than or equal to one
foot, and curve alignment are risk factors for SVROR KA crashes on two-lane rural highways
with moderate-volume. The analysis for high-volume group shows similar results as that
associated with the moderate-volume group. SVROR KA crashes are over-represented on the
segments with 1) 10ft for lane width and a foot for paved shoulder width, 2) 11ft-lane width with
no paved shoulder, 3) less than or equal to 8% truck presence, and 4) the presence of curves.
11
80.0%
74.5%
70.7%
Length
Percent
60.0%
KA Crashes
40.0%
24.7%
28.7%
20.0%
0.8% 0.6%
0.0%
<=10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(a) Low volume (400≤ADT≤700)
80.0%
69.0% 70.0%
Length
KA Crashes
Percent
60.0%
40.0%
27.5% 25.5%
20.0%
3.5% 4.5%
0.0%
<=10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(b) Moderate volume (700<ADT≤1,500)
80.0%
Percent
60.7% 63.1%
Length
60.0%
KA Crashes
40.0%
32.8% 29.8%
20.0%
6.4% 7.1%
0.0%
<=10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(c) High volume (ADT>1,500)
Figure 2-3 SVROR Crashes by Lane and Shoulder Widths on Two-Lane Rural Highways.
12
75.0%
Length
Percent
60.0%
KA Crashes
40.1%
45.0%
43.5%
38.9%
34.1%
30.0%
22.4% 21.0%
15.0%
0.0%
0-8%
9-15%
Truck Presence
>15%
(a) Low volume (400≤ADT≤700)
75.0%
Length
Percent
60.0%
KA Crashes
41.6%
45.0%
30.0%
34.9%
38.5%
28.3% 26.6%
30.0%
15.0%
0.0%
0-8%
9-15%
Truck Presence
>15%
(b) Moderate volume (700<ADT≤1,500)
75.0%
Length
56.2%
60.0%
KA Crashes
Percent
49.6%
45.0%
32.9%
30.0%
30.0%
17.5%
15.0%
13.8%
0.0%
0-8%
9-15%
Truck Presence
>15%
(c) High volume (ADT>1,500)
Figure 2-4 SVROR Crashes by Truck Presence on Two-Lane Rural Highways.
13
100.0%
Length
Percent
80.0%
78.5%
KA Crashes
74.7%
60.0%
40.0%
20.0%
11.7%
17.6%
13.6%
3.9%
0.0%
Curve (R <1000ft)
Curve (R >=1000ft)
Alignment
Straight
(a) Low volume (400≤ADT≤700)
100.0%
Length
Percent
80.0%
KA Crashes
74.7%
65.3%
60.0%
40.0%
21.8% 23.6%
20.0%
11.0%
3.6%
0.0%
Curve (R <1000ft)
Curve (R >=1000ft)
Alignment
Straight
(b) Moderate volume (700<ADT≤1,500)
100.0%
Length
Percent
80.0%
KA Crashes
78.1%
70.4%
60.0%
40.0%
18.2% 19.0%
20.0%
10.6%
3.7%
0.0%
Curve (R <1000ft)
Curve (R >=1000ft)
Alignment
Straight
(c) High volume (ADT>1,500)
Figure 2-5 SVROR Crashes by Alignment on Two-Lane Rural Highways.
14
2.2.2 Risk Factors for Head-on Crashes
For the low-volume group (see Figures 2-6 to 2-8), head-on crashes on two-lane rural highways
are over-represented for 1) a 10ft-lane and a foot paved shoulder width, 2) greater than 15%
truck presence, and 3) curves with less than 1,000ft radius, respectively. For the moderatevolume group, head-on KA crashes are over-represented on two-lane rural highways with risk
factors: 1) a 10ft-lane and a foot paved shoulder width, 2) an 11ft-lane width without paved
shoulder, 3) 9 to 15% truck presence, and 4) curves with less than 1,000ft radius. For the high
volume group, head-on crashes are over-represented on segments with 1) an 11ft-lane width
without paved shoulder, 2) less than or equal to 8% truck presence, 3) greater than 15% truck
presence, and 4) curves with a radius.
15
80.0%
74.5% 74.3%
Length
Percent
60.0%
KA Crashes
40.0%
24.7%
20.0%
20.0%
0.8%
5.7%
0.0%
<=10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(a) Low volume (400≤ADT≤700)
80.0%
69.0%
63.0%
Length
Percent
60.0%
KA Crashes
40.0%
27.5%
31.5%
20.0%
3.5% 5.6%
0.0%
<=10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(b) Moderate volume (700<ADT≤1,500)
80.0%
Length
60.7%
Percent
60.0%
53.3%
KA Crashes
40.2%
40.0%
32.8%
20.0%
6.4% 6.6%
0.0%
<=10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(c) High volume (ADT>1,500)
Figure 2-6 Head-on Crashes by Lane and Shoulder Widths on Two-Lane Rural Highways.
16
75.0%
Length
Percent
60.0%
KA Crashes
43.5% 45.7%
45.0%
34.1% 34.3%
30.0%
22.4% 20.0%
15.0%
0.0%
0-8%
9-15%
Truck Presence
>15%
(a) Low volume (400≤ADT≤700)
75.0%
Length
Percent
60.0%
KA Crashes
41.6%
45.0%
44.4%
30.0% 29.6%
28.3% 25.9%
30.0%
15.0%
0.0%
0-8%
9-15%
Truck Presence
>15%
(b) Moderate volume (700<ADT≤1,500)
75.0%
Length
59.8%
60.0%
KA Crashes
Percent
49.6%
45.0%
32.9%
30.0%
18.9%
17.5%
21.3%
15.0%
0.0%
0-8%
9-15%
Truck Presence
>15%
(c) High volume (ADT>1,500)
Figure 2-7 Head-on Crashes by Truck Presence on Two-Lane Rural Highways.
17
100.0%
Length
Percent
80.0%
78.5%
KA Crashes
62.9%
60.0%
40.0%
20.0%
20.0%
17.6% 17.1%
3.9%
0.0%
Curve (R <1000ft)
Curve (R >=1000ft)
Alignment
Straight
(a) Low volume (400≤ADT≤700)
100.0%
Length
Percent
80.0%
KA Crashes
74.7%
64.8%
60.0%
40.0%
14.8%
20.0%
21.8% 20.4%
3.6%
0.0%
Curve (R <1000ft)
Curve (R >=1000ft)
Alignment
Straight
(b) Moderate volume (700<ADT≤1,500)
100.0%
Length
Percent
80.0%
78.1%
KA Crashes
63.1%
60.0%
40.0%
14.8%
20.0%
18.2%
22.1%
3.7%
0.0%
Curve (R <1000ft)
Curve (R >=1000ft)
Alignment
Straight
(c) High volume (ADT>1,500)
Figure 2-8 Head-on Crashes by Alignment on Two-Lane Rural Highways.
18
2.3 Risk Assessment
In the risk assessment, roadway network elements are prioritized using risk factor weights. Table
2-1 provides the risk factor weights criteria based on the proportion of crash over-representation
and crash total when compared to highway mileage.
Table 2-1 Risk Factor Weight Criteria.
Weight (points)
Category
Crash Total
Crash OverRepresentation
0
1
2
≥0%
≥10
≥20
and
and
and
<10% <20% <30%
>0% ≥2%
0%
and
and
<2% <3%
3
≥30
and
<40%
≥3%
and
<4%
4
≥40
and
<50%
≥4%
and
<5%
5
≥50
and
<60%
≥5%
and
<6%
6
≥60
and
<70%
≥6%
and
<7%
7
≥70
and
<80%
≥7%
and
<8%
8
9
10
≥80
≥90 and
and
100%
<100%
<90%
≥8%
≥9% ≥10%
and
and
and
<9%
<10% ≤100%
Based on the weight criteria in Table 2-1, Tables 2-2 and 2-3 summarize the results of the risk
factor prioritization related to SVROR and head-on KA crashes on two-lane rural highways with
a total pavement width of less than 24ft. The step-by-step process for obtaining the results in
Table 2-2 is presented in Appendix A.
Table 2-2 SVROR Crash Risk Factor Prioritization Results.
Risk Factor
Lane & Shoulder
Width
Truck Percentage
Alignment
10+0
10+1
11+0
≤8%
9-15%
>15%
Curve (R
<1000ft)
Curve (R
≥1000ft)
Straight
Weight (points)
Low Volume
Moderate Volume
(400≤ADT≤700) (700<ADT≤1,500)
7
8
0
1
6
2
2
7
10
3
3
2
High Volume
(ADT>1,500)
8
1
2
11
3
1
8
8
7
1
3
2
7
6
7
19
Table 2-3 Head-on Crash Risk Factor Prioritization Results.
Risk Factor
Lane & Shoulder
Width
Truck Percentage
Alignment
10+0
10+1
11+0
≤8%
9-15%
>15%
Curve (R
<1000ft)
Curve (R
≥1000ft)
Straight
Weight (points)
Low Volume
Moderate Volume
(400≤ADT≤700) (700<ADT≤1,500)
7
6
4
2
2
6
2
2
4
6
6
2
High Volume
(ADT>1,500)
5
1
11
15
1
5
12
11
11
1
2
5
6
6
6
There are two different weight tables—Table 2-2 represents SVROR and Table 2-3 represents
head-on crashes. The total weight (
weight for SVROR,
resulted from combining the different weights (
:
: weight for head-on) is calculated using the following equation:
∗
∗
(1)
Where
= proportion of the number of head-on crashes with respect to SVROR and
= proportion of the crash cost of head-on crashes with respect to SVROR.
From the crash trees (Figures 2-1 and 2-2), there were 6,030 SVROR and 1,665 head-on KA
crashes on two-lane rural highways between 2009 and 2013. Based on these numbers, the
proportion ( ) is 0.276 (=1,665/6,030). The crash cost of the K or A crashes used for the TxDOT
Highway Safety Improvement Program (HSIP) is considered the same. The recommended 2013
crash cost for each K and A crashes is $1,200,000. Although the head-on crashes result in more
K crashes compared to the SVROR crashes, there is no difference between the costs of head-on
and SVROR KA crashes since K and A are assigned the same crash cost. Thus, the crash cost
proportion ( ) is 1.0 (=1,200,000/1,200,000).
Table 2-4 shows the combined results of risk factor weights. For example, 7 points are given to
segments having a 10ft-lane width or less without paved shoulder (i.e., ≤10+0) on low-volume
20
rural highways for each SVROR and Head-on crash type (see Tables 2-2 and 2-3). When those
weights (7 points of
combined weight (
and
and proportions ( : 0.276; : 1.0) are considered in Eq. (1), the
) of ≤10+0 on low-volume rural highways is 8.93 (i.e., 7 + 0.276*1.0*7).
Table 2-4 Combined Crash Risk Factor Prioritization Results.
Weight (points)
Risk Factor
Lane & Shoulder
Width
Truck Presence
Alignment
Low Volume
Moderate Volume
(400≤ADT≤700) (700<ADT≤1,500)
≤10+0
10+1
11+0
≤8%
9-15%
>15%
Curve (R
<1000ft)
Curve (R
≥1000ft)
Straight
High Volume
(ADT>1,500)
8.93
1.10
6.55
2.55
11.10
4.66
9.66
1.55
3.66
7.55
4.66
2.55
9.38
1.28
5.04
15.14
3.28
2.38
11.31
11.04
10.04
1.28
3.55
3.38
8.66
7.66
8.66
2.5 Summary
According to the crash tree analyses with the crashes from 2009 to 2013, SVROR and head-on
KA crashes are dominant crash type in rural areas. Fatal crashes due to a head-on collision
accounted for a half of total head-on KA crashes. The objectives of this report were to identify
risk factors of SVROR and head-on KA crashes on two-lane rural highways with a total
pavement width of less than 24ft and traffic volume of 400 or more vehicles per day and
presented the selection criteria for highway widening projects.
From the comparison using the proportions of crashes and highway mileage, risk factors in
SVROR and head-on KA crashes were first identified. Then, the risk factors for each crash type
were weighted using the proportions based on the crash over-representation and crash total. The
two different weights—one for SVROR and the other for head-on—were combined using an
equation to obtain the total weight. As a result, for low-volume groups, a 10ft-lane width or less
without paved shoulder, 9 to 15% truck presence, and curves with less than 1,000ft radius were
found to be primary risk factors. For moderate- and high-volume groups, a 10ft-lane width or
21
less without paved shoulder, less than or equal to 8% truck presence , and curves with less than
1,000ft radius are identified as primary factors. Especially, highways with less than or equal to 8%
truck presence is a critical factor for high-volume group. A 10ft-lane width or less without paved
shoulder and curves with less than 1,000ft radius are common risk factors for SVROR and headon KA crashes on rural two-lane highways in all traffic volume groups.
22
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Highway and Transportation Officials.
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Safety Manual Knowledge Base." Accessed June 20, 2014.
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Cope, A. J. 1955. "Traffic Accident Experience-Before and After Pavement Widening." Traffic
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Farm-to-Market Roads in Texas." Transportation Research Board 67th Annual Meeting,
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Gross, F., and E. T. Donnell. 2011. "Case–Control and Cross-Sectional Methods for Estimating
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Width: Case-Control Approach." Journal of transportation engineering 133 (6):362-369.
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Shoulder Width Combinations on Rural, Two Lane, Undivided Roads. edited by U.S.
Department of Transportation FHWA. Washington D.C.
Harwood, D., F. M. Council, E. Hauer, W. E. Hughes, and A. Vogt. 2000. Prediction of the
expected safety performance of rural two-lane highways. McLean, Virginia: Midwest
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Harwood, D. W., E. R. K. Rabbani, K. R. Richard, H. W. McGee, and G. L. Gittings. 2003.
"Systemwide Impact of Safety and Traffic Operations Design Decisions for 3R Projects."
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Hauer, E. 2000. "Lane Width and Safety." Accessed June 10, 2014.
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Lyon, and T. Jonsson. 2008. "Methodology to predict the safety performance of rural
multilane highways." Accessed June 20, 2014.
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24
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25
Appendix A
Step-by-Step Process for Risk Factor Prioritization
26
This section presents a step-by-step description of risk factor prioritization. An example is
provided to understand the process. In total, there are five steps in this process.
Step 1. Identify risk factors
The graphs (Figure 2-3 (a)) below show the percentages of highway mileage and SVROR KA
crashes by lane and shoulder width. Only for a 11ft-lane with no shoulder (i.e., 11+0), the
percentage of KA crashes is higher than proportion of highway mileage with that cross-sectional
widths. It means “11+0” is only over-represented risk factor group related to the analysis of lane
and shoulder width for low-volume highways.
80%
74.5%
70.7%
70%
Percent
60%
50%
Over-represented
(higher % of crashes
than % of mileage
length)
Length
KA Crashes
40%
24.7%
30%
28.7%
20%
10%
0.8%
0.6%
0%
10+0
10+1
Lane Width + Shoulder Width (ft)
11+0
(a) Low-volume group
Step 2. Apply crash over-representation weighting criteria
The weighting points are applied to the risk factor groups that are over-represented. Table 2-1
presents weighting points by crash total and crash over-representation. In Step 1, we identified
“11+0” is the only over-represented group for lane and shoulder width in the analysis of SVROR
crashes on low-volume highways. The percentages of SVROR KA crashes and highway mileage
on “11+0” are 28.7% and 24.7%, respectively. It can be concluded that SVROR crashes on
“11+0” are over-represented by 4% (the difference between those percentages). Based on the
crash over-representation weight criteria, 4 points will be counted for “11+0”. For groups that the
percentage of KA crashes is lower than or equal to the percentage of highway mileage, 0 point
will be given to these groups in terms of over-representation criteria.
27
Table 2-1 Risk Factor Weight Criteria
Weight (points)
Category
Crash Total
Crash OverRepresentation
0
1
2
≥0%
≥10
≥20
and
and
and
<10% <20% <30%
>0% ≥2%
0%
and
and
<2% <3%
3
≥30
and
<40%
≥3%
and
<4%
4
≥40
and
<50%
≥4%
and
<5%
5
≥50
and
<60%
≥5%
and
<6%
6
≥60
and
<70%
≥6%
and
<7%
7
≥70
and
<80%
≥7%
and
<8%
8
9
10
≥80
≥90 and
and
100%
<100%
<90%
≥8%
≥9% ≥10%
and
and
and
<9%
<10% ≤100%
Step 3. Apply crash total weighting criteria
The second weighting criterion is related to the percentage of KA crashes. For example, the
percentage of SVROR KA crashes on “11+0” on low-volume highways is 28.7%. Based on the
crash total weight criteria in Table 2-1, 2 points will be given to “11+0”. No point will be given
when the percentage of crashes is less than 10%.
Weight (points)
Category
Crash Total
Crash OverRepresentation
0
1
2
≥0%
≥10
≥20
and
and
and
<10% <20% <30%
>0% ≥2%
0%
and
and
<2% <3%
3
≥30
and
<40%
≥3%
and
<4%
4
≥40
and
<50%
≥4%
and
<5%
5
≥50
and
<60%
≥5%
and
<6%
6
≥60
and
<70%
≥6%
and
<7%
7
≥70
and
<80%
≥7%
and
<8%
8
9
10
≥80
≥90 and
and
100%
<100%
<90%
≥8%
≥9% ≥10%
and
and
and
<9%
<10% ≤100%
Step 4. Sum the weight points of crash over-representation and crash total
From Step 2 and 3, we can obtain the weight points for crash over-representation and crash total.
In this step, the two points are summed. In the case of “11+0”, the points for crash overrepresentation is 4 (Step 2) and the points for crash total is 2 (Step 3). Finally, the total weight
for “11+0” on low-volume ADT is 6 points.
Step 5. Repeat Step 1 to 4 for other risk factors
28
Appendix B
Aggregated Weight Calculations
29
SEGMENT LEVEL WEIGHT CALCULATION
This section presents a 3-step process on how weights were developed for each roadway segment,
where each segment is a homogenous section that may consist of multiple horizontal curves
and/or tangent sections. An example is provided to understand the process.
Step 1. Identify horizontal curves on the segment
The TxDOT’s Geometric (GEO-HINI) database for year 2012 is used to extract the horizontal
curve information on each homogenous roadway segment. A segment is considered
“homogenous” if it has a relatively constant cross section, constant traffic volume, and similar
geometric design features along its length. The control section number and the milepoints are
used to combine the horizontal curves with the roadway segments. An example is provided here.
A roadway segment on FM3363 in Brownwood district exists from DFOs 0.00 to 0.44. It has a
paved width of 22ft with no shoulders, traffic volume of 976 vehicles per day in 2013, and a
truck percentage of 9.8. After merging with the GEO-HINI data, we found that there are 3
horizontal curves on this segment. The first curve starts at DFO 0.129 and ends at 0.152 and has
a radius of 149ft. The second curve with a radius of 1,273ft goes from 0.153 to 0.210, while the
third one, with a radius of 305 ft, starts at 0.349 and ends at 0.408. The properties of various
sections on the segment are summarized below.
Section
Horizontal
Curve 1
Horizontal
Curve 2
Horizontal
Curve 3
Straight
Length
(miles)
Radius
(ft)
0.023
149
0.057
1273
0.059
305
0.301
--
ADT
(veh/day)
Truck
Presence (%)
Lane Width
(ft)
Paved Shoulder
Width (ft)
976
9.8
11
0
Step 2. Apply the risk factor weights
Based on the geometric and traffic variables, the crash risk factor weights are assigned. The
weights based on three volume groups and risk factors are provided in Table 2-4 of the main part
of this report. The particular road segment presented in Step 1 falls under moderate volume
category. The weights based on each risk factor are presented below.
30
Section
Horizontal
Curve 1
Horizontal
Curve 2
Horizontal
Curve 3
Straight
Alignment
Weight (points)
Lane & Shoulder Width
Truck presence
11.04
Total
19.36
3.55
4.66
11.87
3.66
11.04
19.36
7.66
15.98
The total points are calculated by summing the weight points assigned to alignment type, truck
presence, and lane and shoulder width. For example, for horizontal curve 1, total points =
11.04+4.66+3.66=19.36.
Step 3. Calculate aggregated weight
Once individual points are assigned to each section on the segment, a combined weight for the
whole segment is then calculated. The weighted average procedure is used with the weights
based on the section length. The following equation is used to calculate the aggregated weight.
∑
∑
Where,
= Weight (points) awarded to section on the segment;
= Length of section ; and
n = Total number of individual sections on the segment.
The table below shows the aggregated weight calculations.
Section
Horizontal
Curve 1
Horizontal
Curve 2
Horizontal
Curve 3
Straight
Length (
)
Weight (
)
Product of Length and
Weight (
)
0.023
19.36
0.45
0.057
11.87
0.68
0.059
19.36
1.14
0.301
15.98
4.81
31
Sum
0.44
7.08
∑
∑
7.08
0.44
16.08
PROJECT LEVEL WEIGHT CALCULATION
This section presents the weight calculations at a project level. A project can span a few miles
long and may include multiple homogenous segments. It is important to note that the start and
end of a horizontal curve is not considered a change in homogeneity. However, a horizontal
curve will have a different weight than a straight section. This difference is already accounted for
in calculating the weights for homogenous segments. The spreadsheet that is included with this
report has the weights for each and every homogenous segment that has traffic volume of at least
400 vehicles per day and paved width less than 24ft. However, although very rare, some
segments may have been excluded if they have missing or erroneous values. In those situations,
it is recommended to consider the weight of an adjacent segment that has similar properties to
the missing segment. The equation presented in the step 3 of the “segment level weight
calculation” can be used here to calculate the aggregated weight for the project.
∑
∑
_
Where,
= Weight (points) given to homogenous segment ;
= Length of segment ; and
m = Total number of individual homogenous segment included in the project.
32