Cooperative Game Approach to Merging Sequence and Optimal Trajectory Planning of Connected and Automated Vehicles at Unsignalized Intersections

Connected and automated vehicles (CAVs) can improve traffic efficiency and reduce fuel consumption. This paper proposes a cooperative game approach to merging sequence and optimal trajectory planning of CAVs at unsignalized intersections. The trajectory of the vehicles in the control zone is optimized by the Pontryagin minimum principle. The vehicle's travel time, fuel consumption, and passenger comfort are considered to construct the joint cost function, completing the optimal trajectory planning to minimize the joint cost function. Analyzing the different states between neighboring CAVs at the intersection to calculate the minimum safety interval. The cooperative game approach to merging sequence aims to minimize the global cost and the merging sequence of CAVs is dynamically adjusted according to the gaming result. The multi-player games are decomposed into two-player games, to realize the goal of the minimal global cost and improve the calculation efficiency. Compared with the first-in-first-out (FIFO) strategy, the merging strategy of cooperative gaming can reduce fuel consumption. And compared with no control in traffic simulation software, the merging strategy of cooperative gaming can improve the traffic efficiency of the transportation system and reduce fuel consumption.