A Cooperative Merging Strategy for Connected and Automated Vehicles Based on Game Theory With Transferable Utility

Traffic congestion is a serious social problem in modern society, while vehicle merging is one of the main causes of congestion since human driver has to decelerate to avoid collision when merging. Connected and automated vehicles (CAVs) can realize the coordinated merging which will improve the traffic efficiency, reduce the fuel consumption and improve the driving comfort. In this paper, a cooperative merging strategy for CAVs is proposed based on cooperative game theory with transferable utility (TU) and optimal control. By introducing the value of time (VOT), an economic payoff function including time benefit, fuel consumption and driving comfort is constructed. The cooperative game determines the merging sequence (MS) of vehicles and the side payment among them, and can achieve a win-win situation, while the coordinated merging trajectory of each vehicle is computed based on optimal control. The effectiveness and feasibility of the proposed framework are verified though simulation in different cases, and the comparison of simulation results indicates that the proposed framework can improve the economic benefit of vehicles and have the potential for practical application.