A hierarchical path planning algorithm based on graphical search and optimization methods
Liang Wu, Chengzhi Yi, Chao Cheng, Dongxuan Xie · 2023
This paper proposes a hierarchical path-planning algorithm based on a combination of graphical search algorithms and optimization methods. In the global path planning layer, by using the Hybrid A* algorithm, we can quickly obtain an optimal path that can avoid all static obstacles on the map. In the local path planning layer, the global path is optimized by numerical nonlinear numerical optimization to generate a feasible path that satisfies the safety constraints. By processing global path planning and local path planning separately, the computational complexity of path planning can be effectively reduced, and the efficiency and accuracy of the path planning can be improved. Secondly, the hybrid planning algorithm can generate high-quality paths with both safety and flexibility. We simulate and verify the algorithm, and the results show that the method has practical applications in autonomous driving.