Autonomous driving path planning algorithm based on improved A* algorithm in unstructured environment

There are two shortcomings in the application of traditional A* algorithm in the path planning of autonomous driving. One is that the vehicle environment description method suitable for the A* algorithm is not given; the other is that the vehicle contours and kinematic constraints are not considered. Therefore, according to the characteristics of unstructured environment, this paper presents an environment description method combining global navigation layer and local planning layer, and proposes a local motion planning algorithm based on the improved A* algorithm for autonomous driving vehicles in unstructured environment. In the improved algorithm, profile collision is avoided by setting redundant security space, and the cost of path curvature is considered in heuristic function design. Compared with the original algorithm, it can improve the smoothness of the path, so as to get a path more satisfied with vehicle motion constraints. Simulation results show that the improved algorithm can avoid vehicle contours collision and output a smoother path.

Automated summary

This paper introduces an environment description method combining global navigation layer and local planning layer, as well as a local motion planning algorithm based on the improved A* algorithm for autonomous driving vehicles in unstructured environment. The improved algorithm avoids profile collision by setting redundant security space and considers path curvature cost in heuristic function design, resulting in smoother paths and avoiding vehicle contours collision.