Estimating Safety Impacts of Adaptive Signal Control Technology Using a Full Bayesian Approach

Abstract

Adaptive signal control technology (ASCT) is a traffic management strategy that optimizes signal timing based on real-time traffic demand. Although the primary intent of ASCT is to improve the operational performance of signalized intersections, the technology may also have substantial safety benefits. This study explored the potential safety benefits of the ASCT strategy deployed at signalized intersections in Florida, U.S. An observational before-after full Bayes (FB) approach with a comparison group was adopted to develop crash modification factors (CMFs) for total crashes, rear-end crashes, and specific crash severity levels (fatal plus injury [FI], and property damage only [PDO] crashes). The analysis was based on 20 intersections equipped with ASCT and their corresponding 40 comparison intersections without ASCT. The ASCT deployment was found to significantly reduce total crashes by 7.8% (CMF = 0.922), rear-end crashes by 8.7% (CMF = 0.913), and PDO crashes by 8.1% (CMF = 0.919). The 8.6% reduction in FI crashes (CMF = 0.914) was not significant at a 90% Bayesian credible interval. These findings provide researchers and practitioners with an effective means to quantify the safety benefits of the ASCT strategy and conduct economic appraisals of ASCT deployments.