Open AccessA guaranteed collision‐free trajectory planning method for autonomous parking
Author(s) -
Zhang Zhiming,
Lu Shan,
Xie Lei,
Su Hongye,
Li Dongliu,
Wang Qibing,
Xu Weihua
Publication year - 2021
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12028
Subject(s) - trajectory , collision avoidance , collision , computer science , kinematics , frame (networking) , vehicle dynamics , collision detection , mathematical optimization , motion planning , control theory (sociology) , stability (learning theory) , engineering , control (management) , artificial intelligence , mathematics , robot , telecommunications , physics , computer security , classical mechanics , astronomy , machine learning , automotive engineering
Planning a feasible, and safe trajectory is a crucial procedure for autonomous parking which remains to be fully solved. Generally, a trajectory is depicted by a sequence of configurations which include positions, and orientations. However, existing approaches usually design parking trajectories without considering the evolution from one configuration to the next. Hence, these trajectories are practically infeasible in some scenarios, and safety risks may exist. In this paper, a guaranteed collision‐free trajectory planning method is proposed for autonomous parking. A dynamic optimisation problem is built, which includes vehicle kinematics, collision avoidance constraints, and physical restraints. Then the dynamic optimisation problem is discretised into a finite‐dimensional nonlinear programming problem. To describe collision avoidance constraints, the concepts of the virtual protection frame, and the magnification parameter are introduced. It is highlighted that a novel collision detection criterion is raised from the view of geometry. Tests in three common scenarios, and a complex scenario illustrate the effectiveness of the proposed approach. Moreover, the stability of the algorithm is discussed in this paper. Via the proposed approach, an integrated design of planning, and control is possible.