Analysis on safety impact of red light cameras using the Empirical Bayesian approach

Abstract

Traffic signal violations at urban intersections have become a major safety concern in urban areas since, compared to other types of crashes, they may cause a higher percentage of injuries and fatal crashes. Therefore, the deployment of red light cameras has been concentrated on urban intersections, both to prevent traffic signal violations and to reduce vehicle crashes. Other methodologies for establishing the safety impact of red light cameras are also being researched, but accurate results are difficult to ascertain. In this study, the safety impact of red light cameras on urban intersections in Daejeon Metropolitan City, South Korea was assessed using the Empirical Bayesian (EB) approach. According to the EB analysis in this study, red light camera has increased fatal crashes in all crash types by around 2%. However, it has also increased injury crashes in all crash types by about 53%. In specific types of crashes at urban intersections, such as angle, sideswipe & rear-end, and head-on, red light cameras have reduced fatal crashes by around 23%. However, injury crashes for typical crash types at urban intersections have actually increased by around 37%. Furthermore, the EB analysis results of total crashes are similar to those of injury crashes. This may be the result of a higher than average travel speed on arterial link sections in Daejeon compared to that of other metropolitan cities like Seoul. Therefore, the higher average speed on arterial roads may be the cause of the increase of injuries resulting from sideswipe & rear-end crashes.

Keywords:

• Red light cameras
• Safety performance function
• Empirical Bayesian approach
• Safety impacts
• Targeted crash types