Optimal Variable Speed Limit Control in Connected Autonomous Vehicle Environment for Relieving Freeway Congestion
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 4
Abstract
This study presents an optimal variable speed limit (VSL) strategy in a connected autonomous vehicle (CAV) environment for a freeway corridor with multiple bottlenecks. The VSL control was developed by using an extended cell transmission model (CTM) which takes into account capacity decrease and mixed traffic flow, including traditional human-driven cars and heavy vehicles, and autonomous vehicles (AVs). A multiple-objective function was formulated which aims to improve the operational efficiency and smooth the speed transition. A genetic algorithm (GA) was adopted to solve the integrated VSL control problem. A real-world freeway stretch was selected to test the designed control framework. Sensitivity analyses were performed to investigate impacts of both the penetration rate of CAVs and communication range. Simulation performances demonstrated that the developed VSL control not only improves the overall efficiency but also reduces tailpipe emission rate. Simulation results also showed that the VSL control integrating vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and infrastructure-to-vehicle (I2V) communication outperforms the VSL control only. In addition, as the penetration rate of CAVs increases, better performance can be achieved.
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Acknowledgments
The authors express their deepest gratitude to the financial support by the United States Department of Transportation, University Transportation Center through the Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE) at The University of North Carolina at Charlotte (Grant No. 69A3551747133).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 145 • Issue 4 • April 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Apr 2, 2018
Accepted: Sep 24, 2018
Published online: Jan 31, 2019
Published in print: Apr 1, 2019
Discussion open until: Jun 30, 2019
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