Intelligent Vehicle Path Planning Considering Side Slip of Surrounding Vehicles in Icy and Snowy Environment

Under the icy and snowy environment, the road conditions are complex and changeable, especially the reduction of road adhesion coefficient, which brings great challenges to the driving safety of intelligent vehicles. Aiming at the problem that the peripheral vehicle may be unstable at any time in the ice and snow environment, a path planning method considering the side slip of the peripheral vehicle in the icy and snowy environment is proposed in this paper. Firstly, reinforcement learning and artificial potential field are combined to transform the force received by the vehicle in the artificial potential field into the objective function in reinforcement learning for reinforcement learning training. Then, because this paper studies the path planning in the icy and snowy environment, considering that the sideslip of the obstacle vehicle will bring a safety threat to the vehicle, the dynamic rectangular virtual repulsion field of the obstacle vehicle is adjusted accordingly during the sideslip. So that the vehicle will be more repulsed by the obstacle vehicle at this time, and guide the vehicle to avoid the dangerous vehicle in time. Finally, the path planning results are simulated and verified in Matlab / CarSim software. The simulation results show that the path planning method in this paper can effectively make the vehicle avoid obstacles safely and stably, and the planned path meets the dynamic requirements of the vehicle and driving stability.