Automated Conflict Resolution of Lane Change Utilizing Probability Collectives

Lane change is one of the most common maneuvers in traffic. It is a lateral movement which can affect the trajectory of other vehicles, with the possibility of collision. Although the field of autonomous vehicles has been growing and the repertoire of methods used for autonomous navigation is extensive, lane-changing still one of the causes of flow reduction and accidents. Researches usually address the lane change problem from the perspective of a single-agent. On the other hand, multi-agent systems based on interaction among vehicles, equipped with wireless communication technologies, can improve traffic efficiency and safety. This paper presents a multi-agent automated conflict resolution to collision avoidance method based on Probability Collectives to perform coordinated maneuvers in a fully decentralized manner using communication. We used SUMO to simulate lane-changing situations in a two-lane highway scenario, where the vehicles had to do a lane-merging maneuver. We evaluate the time for all vehicles of the platoon complete a lane-merging, vehicle flow per second, maximum string length, and the platoon's average speed. We compared the SUMO centralized lane change method with a fully decentralized PC method. The results show that the PC method closely approximates to the centralized SUMO method which uses all data for its decision making.