TECHBRIEF

Research, Development, 

and Technology

Turner-Fairbank Highway 

Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

https://highways.dot.gov/research

Developing Crash Modification 

Factors for Mini-Roundabouts

FHWA Publication No.: FHWA-HRT-22-109

FHWA Contact: Wei Zhang (ORCID: 0000-0002-5175-7527), 

HRSO-10, (202) 493-3317, wei.zhang@dot.gov

This document is a technical summary of the 

Federal Highway Administration report Developing 

Crash Modification Factors for Mini-Roundabouts 

(FHWA-HRT-23-019).

INTRODUCTION

The Federal Highway Administration’s (FHWA) Development of Crash 

Modification Factors (DCMF) Program was established in 2012 to address

highway safety research needs for evaluating new and innovative safety 

strategies (improvements) by developing reliable quantitative estimates 

of their effectiveness in reducing crashes. Forty-one State departments of 

transportation provided technical feedback on safety improvements to the 

DCMF Program and implemented new safety improvements to facilitate

evaluations. These States are members of the Evaluation of Low-Cost 

Safety Improvements Pooled Fund Study (ELCSI-PFS), which functions 

under the DCMF Program.

The ELCSI-PFS Technical Advisory Committee selected the evaluation 

of mini-roundabout (MR) installations as one of the priorities within its 

purview. MRs are small-diameter roundabouts (50- to 90-ft radii) with 

traversable islands (central island and splitter islands). As a particular 

type of roundabout, MRs are expected to improve traffic operations with 

minimal impact on capacity and reduce the frequency and severity of 

crashes, most likely by curbing right-angle crashes, which are typical at 

stop-controlled and signalized intersections. Previous studies indicated 

the operational benefits of MRs by demonstrating that conversion from 

intersections controlled by all-way stop-control (AWSC) or two-way stopcontrol (TWSC) improved intersection operating efficiency and reduced 

congestion levels (Zhang 2012, 2015). However, a study in South Australia 

found a 62-percent drop in the 85th percentile speeds through intersections 

converted to MRs (Zito and Taylor 1996). Only a few studies have assessed 

the safety effectiveness of MRs based on crash data, most of which were 

conducted outside of the United States. Some before–after studies on MRs 

converted from TWSC indicated a crash reduction of roughly 30–79 percent 

(Green 1977; Lalani 1975; Delbosc et al. 2017).

A before–after safety evaluation study based on actual crash data in the 

United States was challenging because of the limited number of crashes 

at MR locations converted from different types of intersection controls 

(e.g., AWSC, TWSC), a situation that hinders developing reliable crash 
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modification factors (CMFs) for MRs. This TechBrief 

describes the methods and results from an FHWAsponsored study that evaluated the safety benefits of 

MR installations at TWSC and AWSC locations based 

on crash data obtained from multiple MR locations in 

the United States.

Study Objective

The objective of this study was to assess the safety 

effectiveness of MR installations based on crash data 

and develop statistically valid CMFs. The research 

team studied CMFs of MR locations converted from 

both TWSC and AWSC and developed separate CMFs 

for converted MRs from both for various crash types, 

including total, fatal and injury (FI), property damage 

only (PDO), multivehicle total (MV_Total), multivehicle 

FI (MV_FI), and multivehicle PDO (MV_PDO). In 

addition, the researcher provided benefit–cost (B/C) 

ratios for the MR installations. Practitioners can use 

these CMFs and B/C ratios for decisionmaking in their 

project development and safety planning processes.

METHODOLOGY

To compensate for the small number of MR locations

and insufficient crash data available in the United States, 

the researchers used a stronger quasi-experimental

study design that included comparison sites, namely an 

interrupted time series design with comparison groups 

(ITS-CG), and enhanced statistical analysis methods, 

including fully Bayesian (FB) analysis and generalized 

linear mixed models (GLMM). The database included 

three States: Washington, Michigan, and Maryland.

Data

Locations of interest included sites with MR installations 

with known installation dates, entering volumes in 

excess of 800 vehicles per hour, and potentially low 

speed applications. The research team used geographic 

information systems (GIS) tools to prepare, filter, and 

combine data from multiple sources and geolocations 

(typically in shapefile format) (Esri 2019). The research 

team then located nearby sites with the potential to be 

used as comparison sites. This potential was judged 

based on the roadway characteristics (rural or urban), 

surrounding land use (residential, commercial, or 

industrial), facility type (major or minor arterial/

collector), number of lanes in the main road, and 

relative proximity to each MR site. After reviewing all 

candidate sites, the research team selected a set of three 

comparison sites per MR site, and geometry variables 

were collected for each study location (both MR and 

comparison). Table 1 shows the number of MR and 

comparison sites in each of the three States studied. 

After data filtering and assembly, the study included 

15 MR locations from Washington, 6 from Michigan, 

and 6 from Maryland. Crash data from 2003 through 

2019 were available from Washington, data from 

2013 through 2019 from Michigan, and data from 

2015 through 2019 from Maryland.

Table 1. Number of MR and comparison sites 

in three States.

State

Treatment (MR) Sites Comparison Sites

TWSC AWSC Unclear TWSC AWSC

Washington 9 0 6 35 12

Michigan 0 6 0 0 17

Maryland 3 3 0 9 9

To compile annual average daily traffic (AADT) data 

for all sites (including those located in lower functional 

classes) and periods (almost 20 yr at some of the sites 

due to different dates of MR installation) in the study, the 

research team performed AADT data extraction using 

AADT maps and GIS layers available from various 

sources online (Maryland Department of Transportation 

(DOT) 2022; King County 2022; Michigan DOT 2022) 

to obtain the needed AADT figures. The research team 

imputed the missing AADT values when imputation was 

feasible from a trend (i.e., for sites with more than 1 yr 

of AADT available, or for locations where other nearby 

locations had sufficient AADT data available).

The research team collected other site characteristics that 

could be used as additional covariates in the analysis. 

These characteristics included land use, proximity to school 

zones, the presence of a bus stop, bike lanes, crosswalks, 

median type, and signs and markings, among others. Most 

of the MRs and comparison sites were located in urban and 

residential areas; some were located in commercial and 

mixed land use areas.

Safety Analysis

The empirical analyses in this study were conducted using 

the statistical methods appropriate to the characteristics 

of the assembled datasets. Two different analyses were 

performed: FB analysis of crash frequencies using before–

after designs with comparison groups and GLMM for panel 

data using the multistate dataset developed in this research. 

The FB analysis was applied to the Washington data for 

developing CMFs for MRs converted from TWSC, and 

GLMM analysis was applied to a larger dataset consisting 

of three States (Washington, Michigan, and Maryland) for 

MR conversions from both AWSC and TWSC.
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Table 2. CMFs for MRs converted from TWSC for different crash types.

CMFs Total FI PDO MV_Total MV_FI MV_PDO

TWSC CMF 0.6330** 0.5773* 0.5977** 0.6802* 0.5980 0.6389*

Std Dev 0.1512 0.2114 0.1462 0.1621 0.2328 0.1610

95% credible interval (0.3807, 

0.9713)

(0.2616, 

1.0672)

(0.3540, 

0.9341)

(0.4073, 

1.0458)

(0.2556, 

1.1408)

(0.3648, 

1.0109)

90% credible interval (0.4157, 

0.8956)

(0.3019, 

0.9577)

(0.3884, 

0.8623)

(0.4422, 

0.9698)

(0.2966, 

1.0174)

(0.4091, 

0.921)

Crash reduction (percent) 36.70** 42.27* 40.23** 31.98* 40.20 36.11*

*Statistically significant results at 90-percent level.

**Statistically significant results at 95-percent level.

Note: Std Dev represents the posterior Std Dev (uncertainty estimate) for CMF.

FB Analysis of Before–After Data with Comparison 

Groups Based on Washington Data

A safety evaluation due to limited study locations could 

benefit from the incorporation of existing knowledge 

about safety performance of roundabout and stopcontrolled intersections into the evaluation. This strategy 

was considered for the FB analyses to obtain more precise 

CMF estimates. The FB analyses for the Washington data 

were conducted based on the crash data for 2003–2019 

obtained from nine MR locations (with TWSC as the 

intersection type before conversion) for the following 

crash types: total, FI, PDO, MV_Total, MV_FI, and 

MV_PDO. The treatment group for MR with TWSC as 

the before condition in Washington consisted of yearly 

crashes from intersections where MRs were installed 

during 2012, 2013, 2014, 2016, 2017, and 2019. The 

team fitted a Poisson-gamma mixture model that included 

appropriate indicator functions for site type (specifying 

whether a segment is a treatment site or a comparison 

site) and period (specifying whether the site belongs to 

the before- or the after-installation period), as well as the 

time trend for each site type and other covariates to yearly 

crash data. Exposure was accounted for by a log of major 

approach AADT and a log of minor approach AADT. 

Additionally, the researchers included the following 

variables as model covariates:

• Number of approaches.

• PedCross01—Whether there is a pedestrian 

crossing sign: 1 = yes; 0 = no.

• SchoolZone01—Whether there is a school 

zone within 250 ft: 1 = yes; 0 = no.

• diag1—Length of the first diagonal in feet.

• diag2—Length of the second diagonal in feet.

• Speed limit on the major approaches.

To address the issue of the small sample size, the research 

team used an informative prior distribution derived based 

on the CMFs for roundabouts provided on the CMF 

Clearinghouse website (FHWA 2022) and on previous 

studies (Kennedy, Hall, and Barnard 1998; Green 1977; 

Walker and Pitnam 1989; Lalani 1975; Ibrahim and 

Metcalfe 1993) on MRs in the FB analysis. For the prior 

distributions of the other regression coefficients, however, 

proper but diffuse priors were used to reflect the lack 

of precise knowledge on the parameters a priori. The 

inferences on the parameters of interest were made based 

on the samples from the posterior distribution obtained 

by the Markov chain Monte Carlo algorithm.

GLMM Analysis for MR Conversions Based on 

Washington, Michigan, and Maryland Data

The research team conducted safety evaluations of MR 

in the multistate panel data. An explicit account for the 

longitudinal structure and comparison groups was used to 

assess the change in crash frequency at MR installations, 

given the prior traffic control types at those locations.

The research team performed a panel analysis that 

included all data from TWSC and AWSC conversions 

and the corresponding comparison sites. The response 

variables in these analyses were the same as presented 

in the FB analysis. The research team developed overlap 

propensity score weights so the analysis results would be 

indicative of the overlap population between the treated 

and comparison sites.

RESULTS

Safety Effectiveness

Table 2 contains the summary of the results from the 

FB analysis for the MRs converted from TWSC for six 

types of crashes based on the Washington data. The table 

shows the estimated CMFs and the associated uncertainty 

estimates (standard deviation (Std Dev)), 95-percent
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credible intervals, and 90-percent credible intervals, as 

well as the percent crash reduction estimates. The results 

indicate that there were statistically significant reductions 

in total, FI, PDO, MV_Total, and MV_PDO crashes after 

conversion to MRs from TWSC intersections. Reductions 

for total and PDO crashes were statistically significant 

with 95-percent probability, and reductions for FI, 

MV_Total, and MV_PDO crashes were significant with 

90-percent probability.

GLMM Analysis for MR Conversions Based 

on Washington, Michigan, and Maryland Data

Table 3 contains the summary of the results from the 

FB analysis for the MRs converted from AWSC for six 

types of crashes based on the multistate data. Only one 

estimated CMF was found to be statistically significant 

(MV_Total). The CMFs for other crash types and 

severities, however, would all suggest crash reductions, 

but the uncertainties of the CMFs do not provide 

statistical significance.

Economic Effectiveness

The research team estimated MR installation costs based 

on various sources. A Transportation Research Board 

webinar showed a range of MR installations in Michigan 

for 2017 between $840,000 and $900,000 (Gillum 2017). 

According to another source, the installation cost for 

the MRs ranges between $250,000 and $465,000 in 

Texas (Melton and Shumard 2019). Finally, according 

to a 2010 FHWA technical summary, MR construction 

costs are widely dependent on the extent of modification 

to the location necessary for the conversion, as well 

as the materials used in the construction (Rodegerdts, 

Scarbrough, and Bansen 2010). The cost estimates offered 

in 2010 by the FHWA technical summary ranged from 

$50,000 up to $250,000. For the economic evaluation, 

the research team adopted the value of $300,000 in 2020 

to represent a national average.

Economic Effectiveness of MR Installation 

at TWSC

The safety benefit of MR installation is derived from 

the estimated reductions in total crash frequency for 

TWSC conversions (table 2). A statistical life value 

of $11.6 million is the most current value used by the 

U.S. Department of Transportation (Putnam and Coes 

2021). The total yearly benefit (safety only) for MR 

installation at TWSC locations was estimated as $86,290 

in 2020 dollars. In contrast, the 2020 conservative cost of 

construction was estimated as $300,000. For a useful life 

of 10 yr and no salvage value at the end of that period, 

the B/C ratio for the MR installation is estimated as 2.88.

Economic Effectiveness of MR Installation 

at AWSC

The safety benefit of AWSC conversion was estimated 

as the monetary value of reduction in MV_Total crash 

frequencies for AWSC conversions (table 3). The total 

yearly benefits (safety and operational combined) for 

MR installation at AWSC locations was estimated as 

$402,423 in 2020 dollars, whereas the safety-only 

benefit was $86,074, similar to the benefit of TWSC 

intersections. Using the same 2020 cost of construction 

estimate ($300,000) and a useful life of 10 yr with no 

salvage value at the end of that period, the B/C ratio for 

the MR installation at AWSC locations was estimated 

as 13.41 when both safety and operations benefits are 

considered. The B/C ratio was 2.87 when only safety 

benefits were considered.

CONCLUSIONS

The focus of this study was to perform rigorous safetyeffectiveness evaluations of MR installations at TWSC 

and AWSC locations and to develop statistically valid 

CMFs along with uncertainty estimates. The safety data 

for these evaluations were compiled for locations of 

Table 3. CMFs for MRs converted from AWSC based on the multistate data.

Crash Type Estimate Standard Error z Value p Value Significance

Total 0.8813 −0.1263 0.1852 0.4952 —

FI 0.5746 −0.5541 0.4157 0.1825 —

PDO 0.8393 −0.1751 0.1990 0.3788 —

MV_Total 0.6080 −0.4976 0.2455 0.0427 *

MV_FI 0.5422 −0.6122 0.4072 0.1327 —

MV_PDO 0.7710 −0.2600 0.2105 0.2168 —

—Not applicable.

*Significant at the 95.0-percent confidence level.
5

known MR installations around the United States where 

the month of installation and prior intersection condition 

were known. A set of suitable comparison locations 

corresponding to the MR locations was also identified 

to allow the analyses to control for extraneous variables. 

Additionally, geometric features were collected for 

analysis, as well as AADT where available. Model-based 

AADT imputation was performed at locations where 

AADT was partially available and enough for that task. 

The study database included three States (Washington, 

Michigan, and Maryland) and had a longitudinal design, 

including comparison sites, which allowed ITS-CG 

evaluations and a general panel data evaluation.

The analyses were performed using FB analysis of 

before–after (ITS) crash frequency data with comparison 

groups (CG) and binomial GLMMs for the panel 

multistate data. The FB analyses for ITS-CG evaluations 

were carried out based on the Washington crash data for 

MR conversions from TWSC. Crash reductions ranging 

from 31 up to 42 percent were estimated for total, FI, 

PDO, MV_Total, MV_FI, and MV_PDO crash types 

from these analyses. The CMFs for MR converted from 

TWSC intersections were statistically significant for total, 

FI, PDO, MV_Total, and MV_PDO crashes. ITS-CG 

evaluations were also performed on a multistate dataset, 

but this effort produced only one statistically significant 

CMF for MV_Total crashes for AWSC conversions 

(0.61 CMF, or a 39-percent crash reduction).

Finally, the research team performed an economic 

analysis of MR conversions from either AWSC or TWSC. 

Considering both the safety and operational benefits of 

MR installations from AWSC, this analysis produced a 

B/C ratio of 13.41, whereas the B/C ratios were 2.88 and 

2.87 for AWSC and TWSC conversions, respectively, 

when only safety benefits were considered. These results 

indicate the economic feasibility of MR installations.

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Neighborhood Traffic Circles.” Presented at the NCTCOG 

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Analyses—2021 Update.” Official memorandum. 

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JMP Consultants Ltd.

Zhang, W. 2012. “Mini-Roundabout Design and 

Evaluation.” Presented at the Washington State 
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ITE Annual Meeting, Tukwila, WA, June 11, 2012. 

https://www.westernite.org/Sections/washington/

presentations/2012/Mini-Roundabouts.pdf, last 

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Zhang, W. 2015. “Field Testing, Marketing, and 

Crash Analyses of Mini-Roundabouts” (web page). 

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fhwa-presentation.pdf, last accessed August 4, 2022.

Zito, R., and M. Taylor. 1996. “Speed Profiles and Vehicle 

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February 2023 FHWA-HRT-22-109

HRSO-20/02-23(WEB)E

Researchers—This study was performed by Principal Investigator Raul Avelar, along with Eun Sug Park, and 

Boniphace Kutela, Texas A&M Transportation Institute.

Distribution—This TechBrief is being distributed according to a standard distribution. Direct distribution is being 

made to the FHWA divisions and Resource Center.

Availability—This TechBrief may be obtained at https://highways.dot.gov/research.

Key Words—Safety, crash modification factors, CMFs, mini-roundabouts, crashes, stop controlled.

Notice—This document is disseminated under the sponsorship of the U.S. Department of Transportation (USDOT) in 

the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained 

in this document. The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers’ 

names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement—The Federal Highway Administration (FHWA) provides high-quality information to 

serve the Government, industry, and the public in a manner that promotes public understanding. Standards and policies 

are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically 

reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

Recommended citation: Federal Highway Administration, 

Developing Crash Modification Factors for Mini-Roundabouts

(Washington, DC: 2023) https://doi.org/10.21949/1521939