An optimized path planning approach for automatic parking using hybrid A* bidirectional search

Path planning in automatic parking is a significant challenge due to constrained parking spaces and numerous obstacles. To enhance both the safety and efficiency of the planned path, this paper proposes a bidirectional hybrid A* algorithm for narrow spaces with a high density of obstacles. A vehicle obstacle avoidance method that incorporates rectangular expansion through numerical analysis is proposed to achieve collision-free navigation. Meanwhile, a safety cost is integrated into the hybrid A* search algorithm to maintain a sufficient safety distance between the planned path and obstacles. Additionally, to enhance the efficiency of path planning, a bidirectional search method is combined with the hybrid A* algorithm, with the addition of a bidirectional cohesive item cost. Finally, simulation experiments are conducted to generate parking paths for both vertical and parallel parking scenarios. The simulation results indicate that the proposed algorithm obtains a sufficient safety distance, reduced search time, and fewer expanded nodes. Meanwhile, the stability and adaptability of the proposed method are analyzed. The comparison with other algorithms suggests that the proposed algorithm provides a larger safety distance and shorter search time.