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UAV Route Planning Model and Algorithm Considering Time Windows and Multi-Surveillance for Traffic Surveillance

机译:考虑时间窗和多监视的无人机航路规划模型和算法

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This paper introduced the unmanned aerial vehicle (UAV) to conduct road traffic surveillance, and proposed a multi-objective mathematical model for UAV route planning. This model considered the UAV multi-surveillance for one target and used the number of UAVs available, the maximum UAV cruise distance and the time windows of targets as constraints, aiming to minimize the number of UAVs used and the total generalized UAV cruise distance. Then, a multi-objective evolutionary algorithm was proposed. Next, a battery-powered UAV flight experiment was conducted. In addition, a case study with four scenarios was implemented to analyze the impact of UAV multi-surveillance for one target on route planning. The case results showed that compared with the optimal initial solutions, two optimization objectives were improved significantly. Furthermore, with increasing UAV surveillance times for one target, the two objective values increased. Finally, some conclusions and discussions of using UAVs for traffic surveillance were provided.
机译:介绍了无人机进行道路交通监控的方法,并提出了用于无人机航路规划的多目标数学模型。该模型考虑了针对一个目标的无人机多监视,并以可用的无人机数量,最大无人机巡航距离和目标时间窗口为约束条件,旨在最大程度地减少使用的无人机数量和总的通用无人机巡航距离。然后,提出了一种多目标进化算法。接下来,进行了电池供电的无人机飞行实验。此外,还进行了一个包含四个场景的案例研究,以分析无人机多监视对一个目标对航线规划的影响。实例结果表明,与最优初始解相比,两个优化目标得到了明显改善。此外,随着对一个目标的无人机监视时间的增加,两个目标值也随之增加。最后,提供了使用无人机进行交通监控的一些结论和讨论。

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