Optimal Hybrid Path Planning Considering Dynamic and Static Characteristics of Intelligent Vehicles

Aiming at the global path planning of intelligent vehicles, an optimal hybrid path planning algorithm considering the dynamic and static characteristics of intelligent vehicles is proposed. On the grid map with known static information of the environment, the improved A* algorithm is used for global path planning, and the obstacles in the path are expanded according to the static characteristics of the intelligent vehicle itself. Combined with the dynamic characteristics of the intelligent vehicles, dynamic window approach is used to carry out the local obstacle avoidance and path planning of the vehicle according to the unknown and varied environmental information around the vehicle. On this basis, the key turning point in the global path is used as the sub-target point correction of Dynamic Window Approach (DWA). The simulation results show that the proposed method can be used to avoid dynamic and static obstacles by guiding the vehicle to the target ending. Additionally, the dynamic constraints of the vehicle are satisfied during the journey without collision with the road boundary, which ensures the stability and safety of the vehicle.