Trajectory-Based Signal Control in Mixed Connected Vehicle Environments
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 5
Abstract
The emerging connected vehicle (CV) technology has introduced the opportunity to improve traditional traffic signal operation. Real-time vehicle trajectory information (location, speed, and heading) from CV technology can provide information about the nearby traffic conditions which potentially can be utilized for enhanced traffic signal control operation. However, implementation of CV technology still is impractical due to the lower penetration rate of CV-enabled vehicles on the road and the limited deployment of vehicle-to-infrastructure (V2I) communications. This paper developed an approach to use vehicle trajectory data with traditional traffic signal controllers to improve intersection operational performance, even with the limited use or absence of V2I communications. Two signal control algorithms, the delay-based algorithm (DBA) and the weighted delay-based algorithm (WDBA), were developed to demonstrate delay optimization at a signalized intersection. The intersection was modeled in Vissim microsimulation, and simulation scenarios were tested for various traffic demands. Analysis results showed that both proposed algorithms outperformed existing free timing operation, and statistically significant improvement was observed in terms of vehicle delay, stop delay, and queue length.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The research team heavily acknowledges the team from Southern Lighting and Traffic Systems, including Mark Zinn, Bill Leitzan, and Jamie Jones. The research team is thankful for the support and collaboration from the Alabama Department of Transportation and Tuscaloosa Department of Transportation.
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© 2021 American Society of Civil Engineers.
History
Received: Aug 6, 2020
Accepted: Nov 30, 2020
Published online: Feb 25, 2021
Published in print: May 1, 2021
Discussion open until: Jul 25, 2021
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