Search-Based Path Planning Algorithm for Autonomous Parking:Multi-Heuristic Hybrid A*

TL;DR

This paper introduces a Multi-Heuristic Hybrid A* algorithm for autonomous parking that efficiently generates collision-free paths considering vehicle constraints, outperforming traditional Hybrid A* in simulations.

Contribution

The paper presents a novel Multi-Heuristic Hybrid A* algorithm combining features of Multi-Heuristic A* and Hybrid A* for improved autonomous parking path planning.

Findings

Proposed method guarantees completeness and avoids local minima.

Achieves shorter computation times compared to Hybrid A*.

Demonstrates superior performance in simulation experiments.

Abstract

This paper proposed a novel method for autonomous parking. Autonomous parking has received a lot of attention because of its convenience, but due to the complex environment and the non-holonomic constraints of vehicle, it is difficult to get a collision-free and feasible path in a short time. To solve this problem, this paper introduced a novel algorithm called Multi-Heuristic Hybrid A* (MHHA*) which incorporates the characteristic of Multi-Heuristic A* and Hybrid A*. So it could provide the guarantee for completeness, the avoidance of local minimum and sub-optimality, and generate a feasible path in a short time. And this paper also proposed a new collision check method based on coordinate transformation which could improve the computational efficiency. The performance of the proposed method was compared with Hybrid A* in simulation experiments and its superiority has been proved.