文章基本信息

标题：Trajectory Planning in Traffic Scenarios Using Support Vector Machines
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作者：Mahdi Morsali ; Jan Åslund ; Erik Frisk 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：5
页码：91-96
DOI：10.1016/j.ifacol.2019.09.015
语种：English
出版社：Elsevier
摘要：AbstractFinding safe and collision free trajectories in an environment with moving obstacles is central for autonomous vehicles but at the same time a complex task. A reason is that the search space in space-time domain is very complex. This paper proposes a two-step approach where in first step, the search space for trajectory planning is simplified by solving a convex optimization problem formulated as a Support Vector Machine resulting in an obstacle free corridor that is suitable for a trajectory planner. Then, in a second step, a basic A* search strategy is used in the obstacle free search space. Due to the physical model used, the comfort and safety criteria are applied while searching the trajectory. The vehicle rollover prevention is used as a safety criterion and the acceleration, jerk and steering angle limits are used as comfort criteria. For simulations, urban environments with intersections and vehicles as moving obstacles are constructed. The properties of the approach are examined by the simulation results.
关键词：KeywordsAutonomous VehiclesTrajectory planningLearning in autonomous vehiclesSupport vector machines