Number 322 March 2007

Traffic Safety Facts

Traffic Tech – Technology Transfer Series

Automated Enforcement: A Compendium of 

Worldwide Evaluations of Results

U.S. Department of Transportation 400 Seventh Street SW., Washington, DC 20590

National Highway Traffic Safety Administration

Excessive speeding, red-light-running, and other highrisk behaviors are often associated with crash fatalities

and injuries in the United States. Traditional law enforcement alone is not enough to deter high-risk driving behaviors. Automated enforcement systems (AES)

use image-capture technology to monitor and/orto enforce traffic control laws. The goal of AES is to significantly increase the perceived chance of being caught,

thus creating a change in behavior that will translate

into a crash reduction.

TransAnalytics, LLC, prepared a compendium of automated enforcement approaches and systems implementedaroundtheworldforNHTSAandcharacterized

the impacts, based on available research literature.

Methods

A systematic information and literature search of electronic databases from vendors and technical libraries,

Internet sources, and contacts with professional association members yielded a large quantity of national and

international AES evaluation studies. The studies were

then filtered and ranked according to: (1) study methodology; (2) outcome measures; (3) number of treatment

and comparison sites; (4) other treatment characteristics; (5) other evaluation features; and (6) confounding

variables. These factors were used in deciding which

studies should be included in the compendium.

The literature review focused on two specific technologies, speed enforcement and red-light cameras.

Automated speed enforcement systems include fixed 

cameras that monitor traffic speeds without a human operator, or mobile camera operations deployed

in vehicles by law enforcement agents. A third, less

common type of automated speed enforcement is

“speed-over-distance” systems that calculate vehicle

speeds based on start- and end-point times. Red-light

cameras photograph vehicles that enter intersections

after signals have turned red. Offenses can be detected

through sensors buried in the pavement that are tied

to a timing system that integrates the traffic signal and 

pole-mounted camera. In both technologies, photographs of illegal behaviors and license plate numbers

are taken and reviewed by the jurisdiction, usually by

a law enforcement office. Then, the vehicle owner may 

receive a citation.

Research Findings

About 90 studies from 16 countries were identified as 

potential evaluation studies of automated speed enforcement applications; 40 were evaluation studies.

About 75 studies from 9 countries were identified as 

potential evaluation studies of automated red-lightrunning enforcement; 44 were determined to be evaluation studies. Retrospective studies (literature reviews,

meta-analyses, and systematic reviews from the past

two decades) were also reviewed.

The studies generally reported safety benefits, but program parameters, sampling and evaluation methodologies varied so much that safety effects reported cannot

be generalized. A lack of control for regression-to-the

mean effect in most of the studies, along with other

design issues, may have resulted in overestimation of

program benefits.

In the area of automated speed enforcement, 13 key 

studies met the final inclusion criteria. About half of 

these studies documented reductions in speeds as well

as crashes, demonstrating a possible relationship between the treatment and observed safety effect. The

best-controlled fixed-camera speed enforcement sites 

reported estimates of injury crash reductions of 20 to 25

percent. For mobile enforcement programs, two studies looked at system-wide effects and found reductions

in crashed of 25 to 30 percent in daytime unsafe-speedrelated crashes and daytime injury crashes.
TRAFFIC TECH is a publication to disseminate information about traffic safety programs, including evaluations,

innovative programs, and new publications. Feel free to

copy it as you wish. If you would like to receive a copy, contact Melissa Cheung, MPH, Editor, fax 202-366-7096, e-mail: 

melissa.cheung@dot.gov. 400 Seventh Street SW., NTI-130

Washington, DC 20590

For red-light-camera enforcement, seven studies fit the 

evaluation criteria. Overall, key studies supported the

notion that red-light cameras can reduce crash severity at intersections with high red-light-running. The

reviewed studies demonstrated crash effects consistent

with results in previous red-light-camera evaluation

studies, specifically a decrease in right-angle crashes, 

and an increase in rear-end crashes. Several studies

included economic effects analysis based on an aggregation of right-angle and rear-end crash costs for various injury severity levels. These studies demonstrated

thatred-light cameras do provide a moderate aggregate

crash-cost benefit and contribute to decreasing fatal and 

injury angle and left-turn crashes.

Discussion

Existing research suggests that AES can improve safety

at high-crash locations. Based on the limited existing

evidence, covert mobile enforcement programs seem

to result in safety improvements. However, the exact

magnitude of the safety gain, how farit will extend, and

how much it will reflect a change in the targeted behavior (e.g., a decrease in speed) rather than to another

behavior change (e.g., choosing an alternate route) are

still uncertain.

Considerations for future implementations and research of speed and red-light-running AES include: 

(1) designing controlled, randomized experiments; (2) 

critical selection of treatment and matched control locations; (3) applying empirical Bayes methods to the calculation of treatment effects to provide more reliable

estimates; (4) assessing crash severity data to gauge

safety impacts; and (5) investigating strategies to maximize AES benefits.

How to Order

To order the report Automated Enforcement: A Compendium of Worldwide Evaluations of Results, (119 pages), 

prepared by TransAnalytics, write to the Office of 

Behavioral Research, NHTSA, NTI-130, 400 Seventh 

Street SW., Washington, DC 20590, fax 202-366-7096

or download from www.nhtsa.dot.gov. Kathy Sifrit,

Ph.D. was the contracting officer’s technical representative for this project.