Research on Path Planning of Driverless Vehicle Based on Improved A* Algorithm

In view of the shortcomings of the traditional A* algorithm, such as multiple expansion nodes, a large angle of path inflection point and an uneven path, the evaluation function is improved from the heuristic function and the dynamic weighting method is used on the basis of the traditional A* algorithm and the Bessel curve is used to smooth the planned path. The traditional A* algorithm and the improved A* algorithm are simulated and analyzed in Python environment and the improved A* algorithm is applied to the path planning of the left turn condition of the driverless vehicle at the intersection. The results show that the improved A* algorithm reduces the search expansion nodes, so that the search speed is improved, the search time is shortened and the path is smoother.