Fusing improved A* algorithm and dynamic window approach for autonomous driving path planning
This paper proposes a fusion algorithm that combines the improved A* algorithm and dynamic window approach to address the needs of global optimal,time optimal,and obstacle avoidance in autonomous driving path planning.The A* algorithm is improved from four aspects:heuristic function,weight coefficient,search neighborhood,and search strategy while the dynamic window approach mainly improves the evaluation function.The improved A* algorithm and bidirectional A* algorithm are employed to complete global path planning on the grid map.Then,redundant nodes are removed,and the optimized global path is smoothed.Finally,the dynamic window approach is integrated to perform local path planning and obstacle avoidance.Compared with the traditional A* algorithm,the improved A* algorithm and bidirectional A* algorithm significantly reduce the time consumption and nodes in searching for global paths.The fusion algorithm of the optimized A* algorithm and dynamic window approach achieves a higher efficiency and an improved ability in path planning and obstacle avoidance.
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