Safety Evaluation of an Adaptive Signal Control Technology Using an Empirical Bayes Approach

Abstract

Adaptive signal control technology (ASCT) is a traffic management strategy that optimizes signal timing based on actual traffic demand. Although meant to improve the operational performance of signalized intersections, such mobility enhancements may translate into substantial safety benefits. This study examined the safety effects of ASCT using an observational before–after empirical Bayes (EB) approach with a comparison group. The proposed approach was used to develop crash modification factors (CMFs) for total crashes, angle crashes, rear-end crashes, and specific crash severity levels [fatal or injury (FI) and property damage only (PDO) crashes]. The analysis included 42 treatment intersections with ASCT and their corresponding 47 comparison intersections without ASCT. Findings from the study indicated the potential of ASCT to improve the safety of signalized intersections since the CMFs for both ASCT systems (InSync and SynchroGreen) showed significant reductions in crashes. On average, the deployment of ASCT was found to significantly reduce the total, rear-end, FI, and PDO crashes by 5.2%, 12.2%, 4.2%, and 5.7%, respectively. These results were consistent between the two systems. Also, a 2.1% reduction in angle crashes was observed, although the reduction was not statistically significant at a 95% confidence level. The findings from this study provide researchers and practitioners with an effective means to quantify the safety benefits of ASCT and conduct an economic appraisal of ASCT systems.