Improved Hybrid A-Star Algorithm for Path Planning in Autonomous Parking System Based on Multi-Stage Dynamic Optimization

The recent proliferation of intelligent technologies has promoted autonomous driving. The autonomous parking system has become a popular feature in autonomous driving. Hybrid A-star algorithm is a commonly used path planning algorithm for its simplicity to deploy and the good characteristics of the generated paths in the practical engineering. To further enhance the path safety and efficiency of path planning in the autonomous parking system, this paper proposes an improved hybrid A-star algorithm through the safety-enhanced design and the efficiency-enhanced design. The safety-enhanced design integrates the Voronoi field potential into the path searching stage to take more account of path safety. The efficiency-enhanced design proposes a multi-stage dynamic optimization strategy which divides the path planning into multiple stages and performs dynamic optimization in each stage. Through simulation experiments, it is verified that the proposed improved algorithm not only generates a much safer path which stays farther from the obstacles but also significantly improves the searching efficiency in terms of time and space, merely at a finite cost of pre-processing work which can also be repeatedly utilized. We hope this paper will promote relative research on path planning in autonomous parking and serve as a reference for the practical engineering.