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UAV Aided Dynamic Routing of Resources in a Flood Scenario

机译:UAV在洪水场景中的资源有助于动态路由

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This paper addresses the problem of dynamic routing of resources in a fast-changing flood scenario using land vehicles aided by Unmanned Aerial Vehicles (UAVs). The road network of the area is modelled as a graph network with travel time and road capacities and vehicles containing the resources are routed through the roads from the relief centres, or source nodes, to the disaster affected areas, or destination nodes, by considering the goods as a dynamic flow in the road network. The quickest flow algorithm is initially implemented to solve this basic transportation problem. A team of UAVs survey the flooded area to check the safety of the chosen routes and monitor the status of the vehicles over time. Changes in the routing parameters, which can hinder the transportation process, are communicated and the goods are re-routed by considering the current position of the vehicles spread on the road network as individual sources in the problem and then by applying the earliest arrival flows algorithm for a multiple source problem. Simulations are performed on virtual and real street environments considering various scenarios which show the effectiveness of the methodology.
机译:本文讨论了使用无人驾驶飞行器(无人机)辅助的土地车辆快速变化的洪水情景中资源动态路由问题。该地区的道路网络被建模为具有旅行时间的图形网络,通过考虑到灾难受影响的区域或源节点的路线通过路由到灾难受影响的区域或源节点的道路网络。货物作为道路网络的动态流量。最初实施了最快的流量算法以解决这一基本运输问题。一支无人机团队调查了洪水区域以检查所选路线的安全性,并随着时间的推移监控车辆的状态。传送任何可能妨碍运输过程的路由参数的变化,并且通过考虑车辆在道路网络上的当前位置作为问题的单个来源,通过应用最早到达流量算法来重新路由货物对于多源问题。考虑到展示方法的有效性的各种场景,对虚拟和真实的街道环境进行了模拟。

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