Time-optimal global trajectory planning for autonomous valet parking: An improved hybrid A-star algorithm-based optimization control approach

Engineering notes

Key topics: self-driving, motion planning, trajectory planning, planning, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Autonomous valet parking is an L4-level self-driving technology that solves the “last-mile freedom” of automobile users. Aiming at the motion planning problem involved in the decision-making layer of autonomous valet parking, this article proposes a trajectory planning method that obtains global time optimization by solving the optimization problem. The method is based on the path points obtained by the improved hybrid A-star algorithm as the reference waypoints. The global trajectory planning problem is segmented. In each section, the physical system constraints of the vehicle, the boundary condition constraints, and obstacle avoidance constraints in the parking process are comprehensively considered, and the parking trajectory planning task is described as an optimal control problem. The optimal problem is transformed into a nonlinear programming problem by the numerical optimization method. Finally, the global optimal trajectory is obtained on the basis of ensuring the continuity of state variables and control variables. Simulation experiments verify the effectiveness of the algorithm for horizontal and vertical parking. The real vehicle test shows that the vehicle can be safely, quickly, and accurately parked in the parking space.

Links and sources

• Official / arXiv page
• PDF from original source

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