Abstract: Automated valet parking (AVP) has attracted the attention of industry and academia in recent years. However, there are
still many challenges to be solved, including shortest path search, optimal time efficiency, and applicability of algorithm in
complex scenarios. In this paper, a hierarchical AVP path planner is proposed, which divides a complete AVP path planning
into the guided layer and the planning layer from the perspective of global decision-making. The guided layer is mainly
used to divide a complex AVP path planning into several simple path plannings, which makes the hybrid A* algorithm more
applicable in a complex parking environment. The planning layer mainly adopts different optimization methods for driving
and parking path planning. The proposed method is verified by a large number of simulations which include the verification
of the optimal parking position, the performance of the planner for perpendicular parking, and the scalability of the planner
for parallel parking and inclined parking. The simulation results reveal that the efficiency of the algorithm is increased by
more than 20 times, and the average path length is also shortened by more than 20%. Furthermore, the planner overcomes
the problem that the hybrid A* algorithm is not applicable in complex parking scenarios.

Key words: Automated valet parking · Path planning · Hybrid A* · Visibility graph · Shortest path
')">Automated valet parking · Path planning · Hybrid A* · Visibility graph · Shortest path