Evaluation And Spatial Analysis Of Automated Red-Light Running Enforcement Cameras

Keywords

Driver behavior; Empirical Bayes; Evaluation of red light cameras; Highway safety manual; Safety effectiveness

Abstract

Red light cameras may have a demonstrable impact on reducing the frequency of red light running violations; however, their effect on the overall safety at intersections is still up for debate. This paper examined the safety impacts of Red Light Cameras (RLCs) on traffic crashes at signalized intersections using the Empirical Bayes (EB) method. Data were obtained from the Florida Department of Transportation for twenty-five RLC equipped intersections in Orange County, Florida. Additional fifty intersections that remained with no photo enforcement in the vicinity of the treated sites were collected to examine the spillover effects on the same corridors. The safety evaluation was performed at three main levels; only target approaches where RLCs were installed, all approaches on RLC intersections, and non-RLC intersections located on the same travel corridors as the camera equipped intersections. Moreover, the spatial spillover effects of RLCs were also examined on an aggregate level to evaluate the safety impacts on driver behavior at a regional scale. The results from this study indicated that there was a consistent significant reduction in angle and left-turn crashes and a significant increase in rear-end crashes on target approaches, in addition, the magnitude and the direction of these effects, to a lesser degree, were found similar on the whole intersection. Similar trends in shift of crash types were spilled-over to non-RLC intersections in the proximity of the treated sites. On an aggregate county level, there was a moderate spillover benefits with a notable crash migration to the boundary of the county.

Publication Date

1-1-2015

Publication Title

Transportation Research Part C: Emerging Technologies

Volume

50

Number of Pages

130-140

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.trc.2014.07.012

Socpus ID

85027949938 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85027949938

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