文章基本信息

标题：Autonomous-Vehicle Maneuver Planning Using Segmentation and the Alternating Augmented Lagrangian Method ⁎
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作者：Pavel Anistratov ; Björn Olofsson ; Oleg Burdakov 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：15558-15565
DOI：10.1016/j.ifacol.2020.12.2400
语种：English
出版社：Elsevier
摘要：AbstractSegmenting a motion-planning problem into smaller subproblems could be beneficial in terms of computational complexity. This observation is used as a basis for a new sub-maneuver decomposition approach investigated in this paper in the context of optimal evasive maneuvers for autonomous ground vehicles. The recently published alternating augmented Lagrangian method is adopted and leveraged on, which turns out to fit the problem formulation with several attractive properties of the solution procedure. The decomposition is based on moving the coupling constraints between the sub-maneuvers into a separate coordination problem, which is possible to solve analytically. The remaining constraints and the objective function are decomposed into subproblems, one for each segment, which means that parallel computation is possible and beneficial. The method is implemented and evaluated in a safety-critical double lane-change scenario. By using the solution of a low-complexity initialization problem and applying warm-start techniques in the optimization, a solution is possible to obtain after just a few alternating iterations using the developed approach. The resulting computational time is lower than solving one optimization problem for the full maneuver.
关键词：Keywordstrajectorypath planningmotion planningoptimal controlproblem decompositionvehicle safety maneuvers