A Game Theory-based Model Predictive Controller For Mandatory Lane Change Of Multiple Vehicles

Lane change is receiving attention in academia. Most existing lane changing models are rule-based lane changing models which only assume one-direction impact of surrounding vehicles on the lane-changing vehicle. In fact, lane change is a process of mutual interaction between vehicles due to the complexity and uncertainty of the traffic environment. In this paper, we proposed a multi-vehicle cooperative control approach with a distributed control structure to control model. The innovation of this paper lies in that we proposed a multivehicle cooperative lane changing controller which combines game theory and model predictive control (MPC) based on vehicle to vehicle (V2V) communication; Moreover, we designed a multi-lane vehicle ordering method, and decided the optimal time and acceleration of lane change by considering the mutual interaction between vehicles. Typical scenarios were tested to verify that a lane changing vehicle could interact with other vehicles and change lanes without collision. We verified this approach of lane changing through CarSim and MATLAB cosimulation, and compared it with the conventional rule-based lane change decision controller. Test results show that the controller is capable of changing lanes in a smarter manner and guaranteeing the safety and efficiency of the autonomous vehicle.