期刊
KNOWLEDGE-BASED SYSTEMS
卷 86, 期 -, 页码 11-20出版社
ELSEVIER
DOI: 10.1016/j.knosys.2015.04.016
关键词
Autonomous vehicle; Motion planning; Time optimal control; Simultaneous approach; Dynamic optimization
资金
- 973 Program of China [2012CB720503]
- National Nature Science Foundation [61374167]
- 6th National College Students' Innovation 82 Entrepreneurial Training Program [201210006050]
This paper proposes a motion planner for autonomous parking. Compared to the prevailing and emerging studies that handle specific or regular parking scenarios only, our method describes various kinds of parking cases in a unified way regardless they are regular parking scenarios (e.g., parallel, perpendicular or echelon parking cases) or not. First, we formulate a time-optimal dynamic optimization problem with vehicle kinematics, collision-avoidance conditions and mechanical constraints strictly described. Thereafter, an interior-point simultaneous approach is introduced to solve that formulated dynamic optimization problem. Simulation results validate that our proposed motion planning method can tackle general parking scenarios. The tested parking scenarios in this paper can be regarded as benchmark cases to evaluate the efficiency of methods that may emerge in the future. Our established dynamic optimization problem is an open and unified framework, where other complicated user-specific constraints/optimization criteria can be handled without additional difficulty, provided that they are expressed through inequalities/polynomial explicitly. This proposed motion planner may be suitable for the next-generation intelligent parking-garage system. (C) 2015 The Authors. Published by Elsevier B.V.
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