The Highway Safety Information System (HSIS) is a
multi-State safety database that contains crash, roadway inventory, and
traffic volume data for a select group of States. The participating
States, California, Illinois, Maine, Michigan, Minnesota, North
Carolina, Ohio, Utah, and Washington, were selected based on the quality
of their data, the range of data available, and their ability to merge
the data from the various files. The HSIS is used by FHWA staff,
contractors, university researchers, and others to study current highway
safety issues, direct research efforts, and evaluate the effectiveness
of accident countermeasures.
Summary Report:
Evaluation of Lane Reduction "Road Diet" Measures and Their Effects on
Crashes and Injuries
Table of Contents
"ROAD DIETS" ARE OFTEN CONVERSIONS OF FOUR-LANE UNDIVIDED ROADS INTO
THREE lanes (two through lanes and a center turn lane), as shown in
figure 1. The fourth lane may be converted to bicycle lanes, sidewalks,
and/or on-street parking. In other words, existing space is reallocated;
the overall area remains the same.
Under most average daily traffic (ADT) conditions tested, road diets
have minimal effects on vehicle capacity, because left-turning vehicles
are moved into a common two-way left-turn lane.(1,2) However,
for road diets with ADTs above approximately 20,000 vehicles, there is a
greater likelihood that traffic congestion will increase to the point of
diverting traffic to alternate routes.
Road diets can offer potential benefits to both vehicles and
pedestrians. On a four-lane street, drivers change lanes to pass slower
vehicles (such as vehicles stopped in the left lane waiting to make a
left turn). In contrast, drivers' speeds on two-lane streets are limited
by the speed of the lead vehicle. Thus, road diets may reduce vehicle
speeds and vehicle interactions during lane changes, which potentially
could reduce the number and severity of vehicle-to-vehicle crashes.
Pedestrians may benefit because they have fewer lanes of traffic to
cross, and because motor vehicles are likely to be moving more slowly.
The Federal Highway Administration (FHWA) report Safety Effects of
Marked vs. Unmarked Crosswalks at Uncontrolled Locations found that
pedestrian crash risk was reduced when pedestrians crossed two- and
three-lane roads, compared to roads with four or more
lanes.(3)
 |
| Figure 1. A representative road
diet. |
Although road diet advocates enumerate these potential crash-related
benefits, there has been limited research concerning such benefits. This
study was designed to help fill this gap.
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Methodology
Databases Used
This study evaluated road diets at several locations in California
and Washington. Because both States are part of FHWA's Highway Safety
Information System (HSIS), researchers believed that the necessary
high-quality crash data for a large number of crash, roadway, and
vehicle variables would be available from computerized HSIS files.
However, because all the road diets were found to be on non-State
routes, the data were collected manually from local agency files.
Research Design
Researchers selected a treatment and comparison group, and obtained
data for two time periods: one before and one after treatment
installation. The road diets (i.e., treatment sites) were matched with
four-lane streets that were otherwise similar (i.e., comparison sites).
Researchers then obtained crash data for four groups:
1) Road diets-before period.
2) Road diets-after period.
3)
Comparison sites-before period.
4) Comparison sites-after period.
Most comparison sites were four-lane undivided roads that were near
the road diets (such as a parallel road one or two blocks away, or a
perpendicular road). A few comparison sites were four-lane undivided
sections of the same road beyond the location where the road diet was
installed. The comparison sites were selected to be similar to the road
diets in terms of roadway functional class, type of development (e.g.,
commercial or residential), speed limit, intersection spacing, and
access control.
Site Selection
Local traffic engineers in California and Washington were contacted
to determine where road diets were located. Road diets were identified
in eight cities: Bellevue, WA, Mountain View, CA, Oakland, CA,
Sacramento, CA, San Francisco, CA, San Leandro, CA, Seattle, WA, and
Sunnyvale, CA. These are not the only cities in California and
Washington that have road diets, but they are the locations that the
local traffic engineers provided.
Researchers identified candidate comparison sites by reviewing maps
and talking to local traffic engineers. The final list of sites
contained 30 road diets and 50 total matching comparison sites in 8
cities. Because of missing crash data, only 12 road diets and 25
comparison sites are included in this analysis, as described below. The
road diet sections ranged from 0.13-4.09 kilometers (km) (0.08-2.54
miles (mi)). The comparison sites sections ranged from 0.21-4.88 km
(0.13-3.03 mi).
Data Collection
Local traffic engineers provided crash and ADT data for the road
diets and comparison sites. At most locations, 1 or more years of data
were obtained for each of the before and after periods. The actual time
periods varied considerably from site to site, depending on how much
data the city had available and when the road diet was installed.
Because all four seasons were represented, seasonal variations in
crashes were taken into account.
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Analysis
As noted above, researchers initially obtained crash data for 30 road
diets and 50 comparison sites. However, many locations had small sample
sizes of crashes because of short segment lengths, short data periods,
or low ADTs. Therefore, a subset of 12 road diets (2,068 crashes) and 25
comparison sites (8,556 crashes) was chosen for the analyses that are
reported here. These locations generally had segment lengths of at least
0.81 km (0.50 mi). The road diets and comparison sites were placed into
11 groups, each consisting of 1 or 2 road diets and the matching
comparison site(s). The road diets and comparison sites in each group
were located in the same city, thereby accounting for possible
differences in crash-reporting practices among cities. Table 1 lists the
cities, the number of road diets and comparison sites, and the number of
crashes. The before and after analyses were divided into four
categories:
1) Crash frequencies.
2) Crash rates.
3) Crash severity.
4)
Crash types.
Table 1. Study sites and crashes used in the
analysis
| CITY |
NUMBER OF SITES |
NUMBER OF CRASHES |
| Bellevue, WA |
1 |
2 |
134 |
307 |
| Mountain View, CA |
1 |
2 |
20 |
134 |
| Oakland, CA |
2 |
5 |
443 |
2,067 |
| San Francisco, CA |
2 |
5 |
450 |
1,339 |
| Seattle, WA |
5 |
9 |
969 |
4,485 |
| Sunnyvale, CA |
1 |
2 |
52 |
224 |
| Total |
12 |
25 |
2,068 |
8,556 |
| * Each road diet had one or more comparison
sites. |
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Results
Before and After Crash Frequencies
This analysis used 10 groups, with 11 road diets and 24 comparison
sites. One road diet and one comparison site in Seattle, WA, were
excluded because of inconsistent before and after periods.
When researchers pooled data from all 10 groups, a somewhat higher
percent of crashes at the comparison sites occurred in the after period
than at the road diet sites (41.0 percent vs. 35.8 percent). A Cochran-
Mantel-Haenszel test of overall significance across the 10 groups was
statistically significant (X2 1df = 7.5307,
p = 0.0061). The estimated risk ratio indicates the percent of
crashes at road diet sites in the after period to be about 6 percent
less likely than a crash at a comparison site, with 95-percent
confidence limits of 0.003 and 0.106. Thus, on average, crash
frequencies at road diets in the after period were approximately 6
percent lower than at the corresponding comparison sites.
Where before and after ADTs were available, researchers examined
changes on road diets and comparison sites to determine if motorists
were diverting off road diets and onto comparison sites. The ADTs on
four road diets sites increased by 6.4 percent. A slightly higher
increase of 8.0 percent occurred on the 9 matching comparison sites.
Thus, for the sites included in this analysis, any road diet
diversionary effect was limited. Instead, the dominant phenomenon was an
overall increase in ADT as a result of population growth and other
factors.
Crash Rates
The crash rate analysis included 8 groups with reliable ADT data-8
road diets and 14 comparison sites. The ADTs on the road diets ranged
from 8,133-5,658 in the before period and from 8,300-16,482 in the after
period. The ADTs on the comparison sites ranged from 5,480-24,183 in the
before period and from 7,006-26,100 in the after period.
Negative binomial regression models were fit to the crash frequencies
at each site. The explanatory variables were traffic volume (millions of
vehicles), city or alternatively group, site type (road diet or
comparison site), time period (before or after), and a site
type-by-time-period interaction. Segment length was included as a
constant factor (i.e., the number of crashes on a segment was
proportional to its length). More information about negative binomial
regression models can be found in McCullagh and Nelder.(4) (A
later attempt was made to use Empirical Bayes before/after methods as
described by Hauer, but was not possible due to sample
limitations.(5))
The results showed highly significant variation in crash rates with
traffic volume and city, and lesser variation with site type (i.e.,
treatment vs. comparison). The city-by-city variations noted are
probably the result of different operational conditions and
crash-reporting practices.
Figure 2 shows the distributions of crash rates (per million vehicle
miles) for road diets and comparison sites in the before and after
periods. The distributions of crash rates at the road diets were less
variable than those at the comparison sites. The mean crash rates at the
road diets were slightly lower than at the comparison sites. At both the
road diets and comparison sites, the crash rates decreased from the
before period to the after period. The extent of the decrease was
virtually the same at both road diets and comparison sites, and was not
statistically significant. Thus, this rate analysis did not indicate a
significant safety effect.
Crash Severity
The crash severity analysis included 10 groups, with 10 road diets
and 20 comparison sites. The total number of crashes was 7,919. Because
of local reporting practices in San Francisco, CA, many property damage
only (PDO) crashes were not reported. Therefore, two road diets and five
comparison sites in that city were excluded from this analysis.
 |
| Figure2. Crash rates per
million vehicle miles for road diets and comparison
sites. |
A crash was classified as PDO if no injuries and no fatalities
occurred. Otherwise, it was classified as injury and fatality. Overall,
approximately 63 percent (5,007) of the crashes resulted in no injuries
or fatalities. The remaining 37 percent (2,912) of the crashes had at
least one injury or fatality. These percentages were quite similar for
both road diets and comparison sites in both the before and after time
periods. However, injury rates varied somewhat from city to city and
among the matched groups of sites. To account for this variation, a
logistic regression model was fit to the injury severity data (no injury
or injury/fatality). The explanatory variables in the model were:
1) Matched group.
2) Site type (road diet or comparison
site).
3) Time period (before or after).
4)
Site-type-by-time-period interaction.
McCullagh and Nelder Nelder provide an explanation of logistic
regression models.(4)
The results showed that group was the only significant factor
(X2 9df = 347.69, p < 0.0001).
Crash severity was virtually the same at road diets and comparison
sites, and did not change from the before to the after time period. The
city-by-city variations are most likely the result of different
crash-reporting practices in each city.
It was thought that injury and fatal crashes would decrease on road
diets relative to comparison sites, assuming lower vehicle speeds on
road diets in the after period. However, before-and-after speed data
were not available, so it cannot be determined if vehicle speeds
changed. It is possible that road diets could have resulted in fewer
serious (i.e., "A") injuries and more moderate or minor ("B" or "C")
injuries, relative to comparison sites. Such a result would not be
apparent from the crash data, because information on the specific level
of injury was not contained in the data.
Crash Types
Three crash types-angle, rear-end, and sideswipe-accounted for about
80 percent of all crashes (figure 3). Although the crash type
distributions were quite similar for the site-type-by-time-period
interaction, angle collisions were somewhat higher for the road diets,
and perhaps decreased somewhat less in the after period, relative to the
comparison sites.
To investigate this, a logistic regression model was fit to a crash
type variable (angle vs. all other) using the same explanatory variables
as the crash severity model. The results from this model again indicated
a highly significant effect due to group (X2 9df
= 199.24, p < 0.0001). Site type was also statistically
significant (X2 1df = 13.24, p =
0.0003), with the proportion of angle collisions higher on road diets
than on comparison sites. Neither time period nor the
site-type-by-time-period interaction was significant (p = .5862
and p = .9575, respectively). A similar model showed the
proportion of rear-end crashes to be higher for the comparison sites
than for the road diets, again with no significant period or interaction
effects. The only significant effect in a model for sideswipe crashes
was the effect due to group.
 |
| Figure 3. Distribution of crash types for
road diets and comparison sites. |
It is not clear why the crash type distributions were different
between the road diets and the comparison sites, because crash severity
was virtually the same at road diets and comparison sites. One possible
reason is that such differences do exist from one roadway section to
another because of variations in the numbers of driveways and
intersections, vehicle speeds, vehicle mix, area type, and other
factors. It may be that cities selected roadway sections for road diet
installation at least partly because of such factors. The variations in
the crash type distributions among groups may be the result of how each
city classifies and reports crashes. For example, all of the California
cities included angle/turning crashes in the total number of right angle
crashes, but in Bellevue, WA, and Seattle, WA, angle/turning and right
angle crashes were two separate crash types.
Summary of Findings
The key findings of this study are summarized below and in table
2.
1) Crash frequencies at road diets in the after period were
approximately 6 percent lower than at the corresponding comparison
sites.
2) Crash rates did not change significantly from the
before period to the after period. Although crash rates were lower at
road diets than at comparison sites, road diets did not perform better
or worse (from the before period to the after period) relative to
comparison sites.
3) Road diet conversions did not affect crash
severity.
4) Road diet conversions did not result in a
significant change in crash types.
Table 2. Summary of findings.
| ANALYSIS CATERGORY |
COMPARISON
|
| |
Road Diets Before vs. After |
Comparison Sites Before
vs. After |
Before Period Road Diets vs. Comparison
Sites |
After Period Road Diets
vs. Comparison Sites |
| Crash frequency |
Reduction in after period |
No change |
No difference |
Road diets
lower |
| Crash rates |
No change |
No change |
Road diets lower |
Road diets
lower |
| Crash severity |
No change |
No change |
No difference |
No difference |
| Crash type |
No change |
No change |
Difference:
1. Road diets had
a higher percentage of angle crashes.
2. Road diets had a
lower percentage of rear-end crashes. |
Difference:
1.
Road diets had of angle crashes.
2. Road diets had a lower
percentage of rear-end crashes. |
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Conclusions and Recommendations
This study found that a significantly lower (approximately 6 percent)
proportion of crashes occurred at road diets in the after period than at
comparison sites in the after period. However, no significant change was
found in crash rate decreases between road diets and comparison sites.
Thus, one may expect that converting a roadway segment from four-lane
undivided to three lanes likely would reduce total crashes by 6 percent
or less. Road diets were no better or worse than comparison sites with
regard to crash severity.
Additional research is needed to determine whether the crash
reductions observed on road diets can be attributed to lower speeds,
fewer conflicts, or possibly other factors. There is a need for future
safety and operational studies, under a range of traffic volumes and
other conditions, to help identify the situations where road diets would
be appropriate. In addition, traffic operations and capacity must be
considered fully at a given site before implementing road diets and
other lane reduction measures.
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References
- Burden, D. and P. Lagerwey. Road Diets: Fixing the Big
Roads http://wwwcf.fhwa.dot.gov/exit.cfm?link=http://www.walkable.org/download/rdiets.pdf.
Accessed July 25, 2001.
- Welch, T. "The Conversion of Four-Lane Undivided Urban Roadways to
Three-Lane Facilities." Presented at the Transportation Research Board
/ Institute for Transportation Engineers Urban Street Symposium,
Dallas, TX, June 28-30, 1999.
- Zegeer, C.V., J.R. Stewart, H.F. Huang, and P. Lagerwey.
Safety Effects of Marked vs. Unmarked Crosswalks at Uncontrolled
Locations: Executive Summary and Recommended Guidelines.
FHWARD-01-075 Federal Highway Administration, U.S. Department of
Transportation, McLean, VA, 2001.
- McCullagh, P. and J.A. Nelder. Generalized Linear Models.
Chapman and Hall, London, United Kingdom,1989.
- Hauer, E. Observational Before-After Studies in Road
Safety. Pergamon Press, Elsevier Science Ltd., Oxford, United
Kingdom, 1997.
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For more Information
This research was conducted by Herman F. Huang, J. Richard Stewart,
and Charles V. Zegeer of the University of North Carolina Highway Safety
Research Center. The final report, Evaluation of Lane Reduction
"Road Diet" Measures on Crashes and Injuries, can be found in
Transportation Research Record 1784.
For more information about HSIS, contact Carol Tan, HSIS Program
Manager, HRDS, 202-493-3315, carol.tan@fhwa.dot.gov.
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