674
Views
15
CrossRef citations to date
0
Altmetric
Original Articles

Effects of automated speed enforcement in Montgomery County, Maryland, on vehicle speeds, public opinion, and crashes

&
Pages 53-58 | Received 19 Feb 2016, Accepted 09 May 2016, Published online: 02 Sep 2016
 

ABSTRACT

Objectives: In May 2007, Montgomery County, Maryland, implemented an automated speed enforcement program, with cameras allowed on residential streets with speed limits of 35 mph or lower and in school zones. In 2009, the state speed camera law increased the enforcement threshold from 11 to 12 mph over the speed limit and restricted school zone enforcement hours. In 2012, the county began using a corridor approach, in which cameras were periodically moved along the length of a roadway segment. The long-term effects of the speed camera program on travel speeds, public attitudes, and crashes were evaluated.

Methods: Changes in travel speeds at camera sites from 6 months before the program began to 7½ years after were compared with changes in speeds at control sites in the nearby Virginia counties of Fairfax and Arlington. A telephone survey of Montgomery County drivers was conducted in Fall 2014 to examine attitudes and experiences related to automated speed enforcement. Using data on crashes during 2004–2013, logistic regression models examined the program's effects on the likelihood that a crash involved an incapacitating or fatal injury on camera-eligible roads and on potential spillover roads in Montgomery County, using crashes in Fairfax County on similar roads as controls.

Results: About 7½ years after the program began, speed cameras were associated with a 10% reduction in mean speeds and a 62% reduction in the likelihood that a vehicle was traveling more than 10 mph above the speed limit at camera sites. When interviewed in Fall 2014, 95% of drivers were aware of the camera program, 62% favored it, and most had received a camera ticket or knew someone else who had. The overall effect of the camera program in its modified form, including both the law change and the corridor approach, was a 39% reduction in the likelihood that a crash resulted in an incapacitating or fatal injury. Speed cameras alone were associated with a 19% reduction in the likelihood that a crash resulted in an incapacitating or fatal injury, the law change was associated with a nonsignificant 8% increase, and the corridor approach provided an additional 30% reduction over and above the cameras.

Conclusions: This study adds to the evidence that speed cameras can reduce speeding, which can lead to reductions in speeding-related crashes and crashes involving serious injuries or fatalities.

Acknowledgments

The authors thank Captain Thomas Didone and Richard Harrison from the Montgomery County Police Department for providing the speed camera program information and Poppi Venable from the Virginia Department of Motor Vehicles and Ida J. Williams from the Maryland State Police for providing the crash data. We also thank Chuck Farmer and Nate Oesch of the Insurance Institute for Highway Safety for visiting speed data collection sites and overseeing the speed data collection and the conduct of the telephone survey in 2014. Chuck Farmer also provided invaluable guidance regarding the analyses.

Funding

This work was supported by the Insurance Institute for Highway Safety.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 331.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.