Signal and Trajectory Planning for Autonomous Buses at Local Intersections in Bi-modal Traffic Flows

• Published in: 2024 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE International Conference on Robotics, Automation and Mechatronics (RAM) pp. 309 - 314
• Main Authors: Chen, Saifei, Ma, Zhicheng, Jin, Chengqian, Fu, Hui, Qiao, Yan, Wu, Naiqi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 08.08.2024
• Subjects: autonomous buses; Data models; Delays; Microscopy; Optimization models; Planning; speed trajectory planning; system modeling and control; Trajectory planning; transit signal priority; Urban areas
• ISSN: 2326-8239
• DOI: 10.1109/CIS-RAM61939.2024.10673194

Public buses have emerged as an effective way for addressing traffic congestion, energy crises, and emission pollution due to their large occupancy capacities. Furthermore, with the characteristics of fixed-routes and the potential for deploying numerous detection devices without privacy concerns, a bus system becomes a promising candidate for the initial application of autonomous driving technologies. This paper cooperates the control of autonomous buses (ABs) and traffic signals to provide priority for buses in competition with private vehicles, so as to improve the total efficiency of bi-modal traffic flows at signalized intersections from the perspective of passengers. Vehicle flow dynamics for both traffic modes at local intersections are formulated. An optimization model for transit signal priority (TSP) is established for signal planning, where both strategies of green extension and red truncation are considered. Then, speed trajectory planning is conducted for ABs to catch TSP green time. An algorithm is developed to solve the speed of AB platoons. Real data collected from Foshan City in China are utilized to design numerical experiments in a microscopic traffic simulation to verify the effectiveness of the proposed control strategy.