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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.

Evaluation of Lane Reduction

“Road Diet” Measures on Crashes

Summary Report

Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike . McLean, VA 22101-2296

This Highway Safety Information System (HSIS) summary replaces an earlier one, ­Evaluation

of Lane Reduction “Road Diet” Measures and Their Effects on Crashes and Injuries

(FHWA-HRT-04-082), describing an evaluation of “road diet” treatments in Washington and 

California cities. This summary reexamines those data using more advanced study techniques 

and adds an analysis of road diet sites in smaller urban communities in Iowa.

A road diet involves narrowing or eliminating travel lanes on a roadway to make more

room for pedestrians and bicyclists.(1) While there can be more than four travel lanes

before treatment, road diets are often conversions of four-lane, undivided roads into

three lanes—two through lanes plus a center turn lane (see figure 1 and figure 2). The

fourth lane may be converted to a bicycle lane, sidewalk, and/or ­on-street parking. In

other words, the existing cross section is reallocated. This was the case with the two

sets of treatments in the current study. Both involved conversions of four lanes to

three at almost all sites.

Road diets can offer benefits to both drivers and pedestrians. On a four-lane street,

speeds can vary between lanes, and drivers must slow or change lanes due to

­slower vehicles (e.g., vehicles stopped in the left lane waiting to make a left turn).

In ­contrast, on streets with two through lanes plus a center turn lane, ­drivers’

speeds are limited by the speed of the lead vehicle in the through lanes, and

through vehicles are separated from left-turning vehicles. Thus, road diets may

reduce vehicle speeds and vehicle interactions, which could potentially ­reduce

the number and severity of vehicle-to-vehicle crashes. Road diets can also help

­pedestrians by creating fewer lanes of traffic to cross and by reducing vehicle

speeds. A 2001 study found a reduction in pedestrian crash risk when ­crossing

two- and three-lane roads compared to roads with four or more lanes.(2)

Under most annual average daily traffic (AADT) conditions tested, road diets

appeared to have minimal effects on vehicle capacity because left-turning

vehicles were moved into a common two-way left-turn lane (TWLTL).(3,4)

However, for road diets with AADTs above approximately 20,000 ­vehicles,

there is an increased likelihood that traffic congestion will increase to the

point of diverting traffic to alternative routes.

While potential crash-related benefits are cited by road diet advocates, there

has been limited research concerning such benefits. Two prior ­studies were

conducted using data from different urbanized areas. The first, ­conducted

by HSIS researchers, used data from treatment sites in eight cities in

­California and Washington.(5) The second study analyzed data from treatment sites in relatively small towns in Iowa.(6) While the ­nature of the

treatment was the same in both studies (four lanes reduced to three),

the settings, analysis methodologies, and results of the studies ­differed.

­Using a comparison of treated and matched comparison sites before and

after treatment and the development of negative binomial ­regression

models, the earlier HSIS study found a 6 percent reduction in crash

frequency per mile and no significant change in crash rates at the

­California and Washington sites. Using a long-term ­(23-year) crash

history for treated and reference sites and the development of a hierarchical Poisson model in a Bayesian approach, the later Iowa study
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Figure 2. Photo. Three-lane configuration after road diet.

found a 25.2 percent ­reduction in crash ­frequency per mile

and an 18.8 percent reduction in crash rate. Because of these

­differences, ­researchers from the ­National Cooperative Highway ­Research Program (NCHRP) 17-25 project team obtained

and ­reanalyzed both data sets ­using a common methodology.(7)

This summary ­documents the results of that reanalysis.

Methodology

Source: Pedestrian Bike Information Center, 

“Road Diets” training module, 2009.

Research Design

The basic objective of this reanalysis effort was to estimate

the change in total crashes resulting from the conversions

in each of the two databases and to combine these estimates

into a crash modification factor (CMF). To do this, the

empirical Bayes (EB) methodology described by Hauer was

used.(8) A prediction of what would have happened at the

treatment sites in the after period without treatment is based

on aweighted combination of the following two factors:(1)the

frequency of crashes on the treated sites in the before period

and (2) the crash-frequency predictions from regression

models developed with data from similar untreated reference

sites. The prediction of what would have happened without

treatment is then compared to what actually happened with

treatment to estimate the safety effect of the treatment. The

methodology corrects forthe regression bias, changes in traffic

volume at the treatment sites, and other possible confounding

factors aswell as provides a method for combining resultsfrom

different jurisdictions by accounting for differences in crash

experience and reporting practice. Details of the methodology

are in appendix C of NCHRP Report 617.

(7)

Databases Used

The two databases used were obtained from the original study

authors. Both databases provided data on site characteristics

for treatment and comparison or reference sites and on

crashes and AADT for both the before and after periods.

The HSIS study database contained data on treatment and

comparison sites obtained from local traffic engineers in six

cities in California—Mountain View, Oakland, Sacramento,

San Francisco, San Leandro, and Sunnyvale—and two cities

in Washington—Bellevue and Seattle.(5) The data included

30 treatment sites and 51 reference sites. The reference sites

were matched by the local traffic engineer to be similar to the

treatment sites in terms of functional class, type of development, speed limit, intersection spacing, and access control.

The Iowa database included data from the original study for

15 treatment and 15 reference sites from U.S. and State routes

in small urban towns with an average population of 17,000.(6)

These data were supplemented with additional information

provided by the Iowa Department of Transportation for

281 similar reference sites.

As noted earlier, the road diet treatment was very similar at

the sites in both databases. All 15 of the Iowa treatment sites

involved conversion from four lanes to three lanes, with the

third lane being a TWLTL. Bike lanes were installed in only

one case, and parallel parkingwasretained for a sectionwithin

one other site. In the HSIS database, most treatment sites

involved the same conversion from four lanes to three lanes

as at the Iowa sites. At one site, the after condition included

a raised median and left-turn pockets at intersections rather

than a TWLTL.

Table 1 provides descriptive characteristics for the treatment

and control sites from each database. Crash statistics are

also provided. In both data sets, the treatment and reference

segments were divided into “homogeneous sites” for analysis

purposes, and the average length was approximately 1 mi in all

cases. In the Iowa data, the mean AADT for the reference sites

was approximately the same as for the treatment sites, and the

resulting crashes per mile-year for the reference sites and the

before-period treatment sites were very similar. In the HSIS

data, the mean AADT and the crashes per mile-year for the

reference sites were somewhat higher than for the treatment

sites. However, the AADT range in the reference site data

included the AADT range in the treatment data, making it

suitable for the predictive models produced.

Figure 1. Photo. Four-lane configuration before road diet.

Source: Pedestrian Bike Information Center, 

“Road Diets” training module, 2009.
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The EB evaluation of total crash frequency indicated a

statistically significant effect of the road diet treatment in both

data sets and when the results are combined. Table 2 shows

the results from each of the two studies and the combined

results—the CMFs and their standard deviations.

Table 1. Descriptive statistics of evaluation sites

Database/site Type Characteristic Mean Minimum Maximum

Iowa Treatment 

(15 sites)

Years before 17.53 11.00 21.00

Years after 4.47 1.00 11.00

Crashes/mile-year before 23.74 4.91 56.15

Crashes/mile-year after 12.19 2.27 30.48

AADT before 7,987 4,854 11,846

AADT after 9,212 3,718 13,908

Average length (mi) 1.02 0.24 1.72

Iowa Reference 

(296 sites)

Years 21.8 5 23

Crashes/mile-year 26.8 0.2 173.7

AADT 8,621 296 27,530

Average length (mi) 0.99 0.27 3.38

HSIS Treatment 

(30 sites)

Years before 4.7 1.8 8.5

Years after 3.5 0.6 8.8

Crashes/mile-year before 28.57 0.00 111.10

Crashes/mile-year after 24.07 0.00 107.62

AADT before 11,928 5,500 24,000

AADT after 12,790 6,194 26,376

Average length (mi) 0.84 0.08 2.54

HSIS Reference 

(51 sites)

Years 7.82 4.50 12.17

Crashes/mile-year 42.19 5.96 169.73

AADT 15,208 1,933 26,100

Average length (mi) 0.95 0.10 3.31

Analysis

As previously noted, one component of the prediction of afterperiod accident frequencies at the treatment sites without

treatment is a regression model developed using data from the

untreated reference sites. This model is referred to as a safety

performance function (SPF). In this study, generalized linear

modeling was used to estimate the SPF coefficients using the

software package SAS® and assuming a negative binomial

error distribution, all consistent with the state of research in

developing these models. Examination of several model forms

indicated that the most appropriate and useful models for both

databases includedAADT and segment length.The final model

form and coefficients differed for the two databases. The final

model for the Iowa data is shown in equation 1, where ay is

a series of yearly calibration factors developed to account for

the safety effect of changes other than AADT (e.g., accident

reporting practices, demography, weather). 

Results

The final model for the HSIS data is shown in equation 2. The

HSIS data did not allow the development of yearly calibration

factors.

Table 2. Results of the EB analysis for the Iowa and HSIS data concerning 4-lane to 3-lane road diets.(5,6,7)

Crash Type Studied and Estimated Effects

State/ Site Characteristics Accident Type Number of

Treated Sites

CMF

(Standard deviation)

Iowa: Predominately U.S. and State routes within 

small urban areas (average population of 17,000) 

Total crashes 15 (15 mi) 0.53 (0.02)

California/Washington: Predominately corridors 

within suburban areas surrounding larger cities 

(average population of 269,000)

Total crashes 30 (25 mi) 0.81 (0.03)

All sites Total crashes 45 (40 mi) 0.71 (0.02)

Expected number of accidents per year =

ay(length)exp(-8.4439)(AADT)1.2917 (1)

Expected number of accidents per year =

exp(-3.6323)(length)0.7182(AADT)0.5722 (2)
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for more information

REFERENCES

1. Federal Highway Administration 

Office of Safety. (2008). A 

Resident’s Guide for Creating 

Safe and Walkable Communities, 

FHWA-SA-07-016, Washington, 

DC. Obtained from: http://safety.

fhwa.dot.gov/ped_bike/ped_cmnity/

ped_walkguide/resource7.cfm. Site 

last accessed January 5, 2010.

2. Zegeer, C.V., Stewart, J.R., Huang, H.F., 

and Lagerwey, P. (2001). Safety Effects 

of Marked vs. Unmarked Crosswalks 

at Uncontrolled Locations: Executive 

Summary and Recommended Guidelines, 

FHWA-RD-01-075, Federal Highway 

Administration, Washington, DC.

3. Burden, D. and Lagerwey, P. (1999). 

Road Diets: Fixing the Big Roads. 

Obtained from: http://www.walkable.org/

download/rdiets.pdf. Site last accessed 

July 25, 2001.

4. Welch, T. (1999). The Conversion of 

Four-Lane Undivided Urban Roadways 

to Three-Lane Facilities. Presented at the 

Transportation Research Board/Institute 

of Transportation Engineers Urban Street 

Symposium, Dallas, TX.

5. Huang, H., Stewart, J., and Zegeer, C. (2002). 

“Evaluation of Lane Reduction ‘Road 

Diet’ Measures on Crashes and Injuries,” 

Transportation Research Record 1784, 80–90.

6. Pawlovich, M., Wen, L., Carriquiry, A., and Welch, 

T. (2006). “Iowa’s Experience with Road Diet 

Measures: Use of Bayesian Approach to Assess 

Impacts on Crash Frequencies and Crash Rates,” 

Transportation Research Record 1953, 163–171. 

7. Harkey, D., Council, F., Srinivasan, R., Lyon, C., 

Persaud, B., Eccles, K., Lefler, N., Gross, F., Baek, J., 

Hauer, E. and Bonneson, J. (2008). NCHRP Report 

617: Accident Modification Factors for Traffic 

Engineering and ITS Improvements, Transportation 

Research Board, Washington, DC. Obtained from: 

http://www.trb.org/news/blurb_detail.asp?id=8965.

8. Hauer, E. (1997). Observational Before-After Studies 

in Road Safety. Pergamon Press, Oxford, England. 

9. Knapp, K. and Giese, K. (1999). Speeds, Travel Times, 

Delays on US 75 4/3 Lane Conversion through Sioux 

Center, Iowa during the AM and PM Peak Periods. 

Iowa State University/Center for Transportation 

Research and Education for the Iowa Department of 

Transportation, Ames, IA.

FHWA-HRT-10-053

HRDS-06/06-10(1M)E

The Iowa data indicate a 47 percent reduction in total crashes while the HSIS (California and

Washington) data indicate a 19 percent decrease—a substantial difference. These reanalysis

results also differ from the original Iowa study results (a 25 percent reduction) and from the

original HSIS results (a 6 percent reduction).Combining both data sets results in a 29 percent

reduction in total crashes.

The authors identified two likely reasons the reanalysis differed from the original Iowa

results. First, the reanalysis involved a much larger reference group than was available in

the original study. Second, while the results of the original study weighted all treatment

sites equally regardless of length, the reanalysis results provided more weight to longer

sites. While not stated in the reanalysis report, the difference in the two analyses of the

HSIS data could have resulted from the use of improved methodology (the EB method)

in the reanalysis effort. This methodology made it possible to use all 30 treatment sites

and 51 reference sites. In the original study, data from only 11 treatment sites and

24 reference sites were used, with the remaining sites being omitted due to small

sample sizes of crashes because of short segment lengths, short data periods, or low

average daily traffic.

Of more importance than the differences between the original and current

study efforts are the differences between the Iowa and HSIS treatment effects

estimated in the reanalysis effort. These differences may be a function of traffic

volumes and characteristics of the urban environments where the road diets

were implemented. The sites in Iowa ranged in AADT from 3,718 to 13,908

and were predominately on U.S. or State routes passing through small urban

towns with an average population of 17,000. The sites in Washington and

California ranged in AADT from 6,194 to 26,376 and were predominately on

corridors in suburban environments that surrounded larger cities with an

average population of 269,000. In addition, based on a separate study of one

site in Iowa, there appeared to be a traffic calming effect that resulted in

a 4–5 mi/h reduction in 85th percentile free-flow speed and a 30 percent

reduction in the percentage of vehicles traveling more than 5 mi/h over

the speed limit (i.e., vehicles traveling 35 mi/h or higher).(9) The reanalysis

authors speculated that while there could have been significant differences

in speeds between the rural U.S. or State highway approaching a small

town and the road diet section, this calming effect would be less likely in

the larger cities in the HSIS study, where the approaching speed limits

(and traffic speeds) might have been lower before treatment.

Given these differences, it isrecommended that the choice of which CMF

to use should be based on the characteristics of the site being considered.

If the proposed treatment site is more like the Iowa sites (i.e., U.S. or

State routes with moderate AADTs in small urban areas), then the

47 percent reduction found in Iowa should be used. If the treatment

site is part of a corridor in a suburban area of a larger city, then the

19 percent reduction should be used. If the proposed site matches

neither of these site types, then the combined 29 percent reduction

is most appropriate.

Discussion and Recommendations

The research combining both databases was conducted by 

Bhagwant Persaud and Craig Lyon of Ryerson University, 

Toronto, Canada, as part of NCHRP Report 617.(7) The full 

study and appendix C can be downloaded from the Web address 

shown in the reference list. References to the initial studies that 

generated the two databases are also included in that list.(5,6) For 

more information about HSIS, contact Carol Tan, HSIS Program 

Manager, HRDS, (202) 493-3315, carol.tan@dot.gov.

Visit us on the Web 

at www.tfhrc.gov