Cooperation Method of Connected and Automated Vehicles at Unsignalized Intersections: Lane Changing and Arrival Scheduling

• Published in: IEEE transactions on vehicular technology Vol. 71; no. 11; pp. 11351 - 11366
• Main Authors: Chen, Chaoyi, Cai, Mengchi, Wang, Jiawei, Li, Kai, Xu, Qing, Wang, Jianqiang, Li, Keqiang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; arrival time scheduling; Automation; Behavioral sciences; Connected and automated vehicles; Cooperation; intersection management; Intersections; Iterative methods; Job shop scheduling; lane change permitted intersections; Lane changing; Optimal scheduling; Path planning; Processor scheduling; Scheduling; Trajectory; Vehicle-to-everything
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2022.3193096

Connected and automated vehicles (CAVs) have shown great potential in improving traffic efficiency in the area of intersection management. Numerous researches have been accomplished to solve the CAV scheduling problem at the intersection scenario. However, most of them focus on intersections where lane-changing behavior is prohibited, which is impractical for real-world implementation. To address this problem, this paper proposes a novel cooperation framework to solve the CAV arrival scheduling problem in unsignalized intersections where lane changing behavior is permitted. In the first stage, an iterative framework is proposed to solve target assignment and path planning problems, which prevents the deadlock of multiple CAVs with different target lanes. In the second stage, a graph-based minimum clique cover method is then established to obtain the optimal scheduling plan for the CAVs with a low calculation burden. Extensive numerical simulations for different numbers of vehicles and traffic volumes validate the effectiveness of the proposed algorithm.