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Velocity-Based Heuristic Evaluation for Path Planning and Vehicle Routing for Victim Assistance in Disaster Scenarios

机译:基于速度的路径规划和车辆路线的启发式评估,灾害情景

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Natural and human-made disasters require effective victim assistance and last-mile relief supply operations with teams of ground vehicles. In these applications, digital elevation models (DEM) can provide accurate knowledge for safe vehicle motion planning but grid representation results in very large search graphs. Furthermore, travel time, which becomes a crucial cost optimization criterion, may be affected by inclination and other challenging terrain characteristics. In this paper, our goal is to evaluate a search heuristic function based on anisotropic vehicle velocity restrictions for building the cost matrix required for multi-vehicle routing on natural terrain and disaster sites. The heuristic is applied to compute the fastest travel times between every pair of matrix elements by means of a path planning algorithm. The analysis is based on a case study on the ortophotographic DEM of natural terrain with different target points, where the proposed heuristic is compared against an exhaustive search solution.
机译:自然和人为灾害需要有效的受害者援助和与地面车队的最后一英里救济供应业务。在这些应用中,数字高度模型(DEM)可以为安全车辆运动规划提供准确的知识,但电网表示导致非常大的搜索图。此外,成为关键成本优化标准的旅行时间可能受到倾斜和其他具有挑战性的地形特征的影响。在本文中,我们的目标是根据各向异性车辆速度限制来评估搜索启发式功能,用于构建自然地形和灾害站点的多车途路由所需的成本矩阵。启发式致力于通过路径规划算法计算每对矩阵元素之间的最快行进时间。该分析基于对具有不同目标点的自然地形的逆镜头DEM的案例研究,其中拟议的启发式与详尽的搜索解决方案进行比较。

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