Safety Evaluation of an Adaptive Signal Control Technology Using an Empirical Bayes Approach
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 4
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.
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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This project was partially funded by the Florida Department of Transportation (FDOT) and conducted as a cooperative effort by the Florida International University (FIU) and the University of North Florida (UNF). The opinions, results, and findings presented in this manuscript are those of the authors and do not necessarily represent the views of FDOT, FIU, or UNF.
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Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 4 • April 2022
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© 2022 American Society of Civil Engineers.
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Received: May 10, 2021
Accepted: Dec 8, 2021
Published online: Jan 31, 2022
Published in print: Apr 1, 2022
Discussion open until: Jun 30, 2022
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