Fostering cooperative intersection crossing for connected and automated traffic on urban corridors

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Authors
Wei, Yu
Issue Date
2023-05
Type
Electronic thesis
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en_US
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Civil engineering
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Abstract
Connected and automated vehicle (CAV) technologies can revolutionize transportation by eliminating human errors and enabling timely information sharing. The potential of CAVs to improve traffic mobility, safety, and sustainability is substantial, particularly at intersections that often represent significant bottlenecks of roadway networks. However, uncertain traffic flows and intense conflicting movements make vehicle crossing reliability a vital concern. Communication between CAVs and infrastructure can also substantially affect CAV crossing performance at intersections. Hence, ensuring CAV intersection crossing reliability is of utmost importance in this dynamic and complex environment.To tackle these issues, this dissertation aims to foster reliable cooperative intersection crossing for CAV traffic on urban corridors by advancing research in four interrelated areas: (1) Analyzing CAV traffic dynamic behavior focusing on CAV traffic oscillation under perturbation, (2) Investigating the communication side impact on the safety and stability of CAV platoons, (3) Enhancing CAV crossing reliability by adopting the notion of virtual platooning to develop an adaptive cooperative intersection crossing control, and (4) Leveraging the adaptive cooperative control to the corridor level to eliminate potential gridlock due to spatial constraints and traffic demand variations. The findings of this dissertation enhance our understanding of CAV traffic behavior and the impact of vehicle communication on CAV safety and efficiency. The models and control principles developed in this dissertation can help in the design of more effective control strategies at isolated intersections and corridors, as well as inform the development of new approaches to address the challenges and opportunities presented by the rapid development and deployment of CAV technologies.
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May2023
School of Engineering
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Rensselaer Polytechnic Institute, Troy, NY
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