Full Bayesian Before-After Analysis of Safety Effects of Variable Speed Limit System

Abstract

Variable speed limits (VSL) is a major Intelligent Transportation System (ITS) technology for controlling freeway mainline traffic, which have been increasingly used to improve traffic safety and operations efficiency of freeway traffic management. The primary objective of this study is to evaluate the safety impacts of the VSL system implemented on Interstate 5 in Seattle, United States since 2010. A Full Bayesian (FB) before-after analysis was conducted based on 9,787 crashes that occurred in a 72-month study period. The analysis was conducted for all crashes, crash severity levels, crash types, and crash causes. The FB before-after results implied that the total crash count was reduced by 32.23% with a standard deviation of 3.58% after the VSL system was applied on the freeway. The count of crashes with no injury decreased more than crashes with severe injury and possible injury. The effect of rear-end crash reduction was the most beneficial among all crash types, while the effect on sideswipe crash reduction was the least. The study also compared the traffic speed features in the before and after periods to fully evaluate the impacts of the VSL system on traffic operations. The result indicated that, with VSL control, the difference in speed was reduced by the VSL system. The results of this study are particularly valuable for policy and control strategy development, and cost-benefit evaluation associated with VSL system implementations.