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Traffic Patrolling Routing Problem with Drones in an Urban Road System

机译:无人机在城市道路系统中的交通巡逻路径问题

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摘要

The remarkable development of various sensor equipment and communication technologies has stimulated many application platforms of automation. A drone is a sensing platform with strong environmental adaptability and expandability, which is widely used in aerial photography, transmission line inspection, remote sensing mapping, auxiliary communication, traffic patrolling, and other fields. A drone is an effective supplement to the current patrolling business in road traffic patrolling with complex urban buildings and road conditions and a limited ground perspective. However, the limited endurance of patrol drones can be directly solved by vehicles that cooperate with drones on patrolling missions. In this paper, we first proposed and studied the traffic patrolling routing problem with drones (TPRP-D) in an urban road system. Considering road network equations and the heterogeneity of patrolling tasks in the actual patrolling process, we modeled the problem as a double-layer arc routing problem (DL-ARP). Based on graph theory and related research work, we present the mixed integer linear programming formulations and two-stage heuristic solution approaches to solve practical-sized problems. Through analysis of numerical experiments, the solution method proposed in this paper can quickly provide an optimal path planning scheme for different test sets, which can save 9%–16% of time compared with traditional vehicle patrol. At the same time, we analyze several relevant parameters of the patrol process to determine the effect of coordinated traffic patrol. Finally, a case study was completed to verify the practicability of the algorithm.
机译:各种传感器设备和通信技术的惊人发展刺激了许多自动化应用平台。无人机是具有很强的环境适应性和可扩展性的传感平台,广泛用于航空摄影,传输线检查,遥感制图,辅助通信,交通巡逻等领域。无人驾驶飞机是道路交通巡逻中当前巡逻业务的有效补充,因为城市建筑物和道路条件复杂,地面视野有限。但是,在巡逻任务中与无人机合作的车辆可以直接解决巡逻无人机的有限耐久性。在本文中,我们首先提出并研究了城市道路系统中带有无人机的交通巡逻路径问题(TPRP-D)。考虑到道路网络方程式和实际巡逻过程中巡逻任务的异质性,我们将此问题建模为双层弧形路由问题(DL-ARP)。基于图论和相关研究工作,我们提出了混合整数线性规划公式和两阶段启发式求解方法来解决实际规模的问题。通过数值实验分析,本文提出的求解方法可以快速为不同的测试集提供最佳的路径规划方案,与传统的车辆巡逻相比,可以节省9%–16%的时间。同时,我们分析了巡逻过程中的几个相关参数,以确定协同交通巡逻的效果。最后,通过案例研究验证了该算法的实用性。

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