Research on High-Speed Automatic Lane Change Decision-Making and Planning Considering Driving Style
There are insufficient vehicle-vehicle interaction and poor matching between planning and control in the decision-making model of high-speed autonomous vehicles.In order to solve these problems,a closed-loop lane change decision model based on Stackelberg game was constructed.Faulty vehicle response was incorporated into lane changing decision while introducing driving style feature.The multi-objective decision-making cost function was optimized.Particle Swam Optimization(PSO)algorithm was used to solve the game decision model,and the vehicle state was predicted by using a kinematic model that considers the influence of center of mass sideslip angle.A nonlinear model predictive planning controller based on dynamic risk potential field method was designed.The simulation test results show that the closed-loop lane-changing decision-making model proposed in this paper can effectively combine the interaction behavior and driving style characteristics of vehicles to make correct decision-making instructions and implement corresponding motion planning and control.
Autonomous vehicleLane change decision-making and planningDriving styleStackelberg game theory
万方数据
维普
