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Efficient Motion Planning for Autonomous Vehicle Maneuvers Using Duality-Based Decomposition

机译:基于对偶分解的自主车辆操纵的有效运动规划

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摘要

A method to decompose a motion-planning problem into several segments is presented. It is based on a modification of the original problem, such that certain variables at the splitting points are considered to be precomputed and thus fixed and the remaining variables are obtained by performing Lagrange relaxation. The resulting dual problem is split into several subproblems, allowing parallel computation. The method is formalized as a computational algorithm and evaluated in a safety critical double lane-change situation. The resulting maneuver has close-to-optimal behavior and, for certain initialization strategies, it is obtained in shorter computational time compared to computing the full maneuver in one step.
机译:提出了一种将运动计划问题分解为几个部分的方法。它基于对原始问题的修改,因此可以认为拆分点处的某些变量已预先计算并因此被固定,而其余变量则通过执行Lagrange松弛获得。由此产生的双重问题分为几个子问题,允许并行计算。该方法形式化为计算算法,并在安全关键的双车道变更情况下进行评估。所产生的动作具有接近最佳的行为,并且对于某些初始化策略而言,与一步计算完整动作相比,它可以在更短的计算时间内获得。

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