Optimization-Based Approach for Resilient Connected and Autonomous Intersection Crossing Traffic Control Under V2X Communication

• Published in: IEEE transactions on intelligent vehicles Vol. 7; no. 2; pp. 354 - 367
• Main Authors: Lu, Qiang, Jung, Hojin, Kim, Kyoung-Dae
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.06.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Connected and autonomous vehicle; Delays; mixed integer programming (MIP); Optimization; resilient intelligent intersection management; Safety; Schedules; Traffic control; Traffic intersections; Traffic signals; Traffic volume; Trajectory; V2X communication; Vehicle-to-everything; Wireless communication
• ISSN: 2379-8858; 2379-8904
• DOI: 10.1109/TIV.2021.3133841

In this paper, we present an optimization-based approach for safe, efficient, and resilient autonomous intersection traffic control in realistic vehicle-to-everything (V2X) communication environment. The proposed framework produces the fastest discrete-time trajectory for vehicles who want to cross an intersection. Constraints for safety are designed carefully in the optimization problem formulation to prevent potential collisions during intersection crossings. A novel vehicle-to-intersection (V2I) interaction mechanism is designed to handle imperfect communication characteristics such as packet delivery delay and loss. The proposed intersection management framework is evaluated by running extensive simulations using an open source vehicular network and microscopic traffic simulation software, Veins. The results show that the overall traffic control performance of the proposed framework is substantially better than conventional traffic light control framework, in particular when traffic volume is light and medium, even in situations with a realistic wireless vehicular network setting where packet delivery delays and drops occasionally occur.