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A Multi-Trip Vehicle Routing Problem for Small Unmanned Aircraft Systems-Based Urban Delivery

机译:基于小型无人飞机系统的城市运输多行程车辆路径问题

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摘要

With the emergence of new technologies for small unmanned aircraft systems (sUAS), such as lightweight sensors and high-efficiency batteries, the operation of small unmanned aerial vehicles (sUAVs) will expand from military use to commercial use. A promising commercial application of sUAS is package delivery because of its potential to reduce acquisition and operating costs of the last-mile delivery system, while enabling new services such as same-day delivery. Moreover, in urban areas, sUAVs can deliver packages to customers without negatively affecting street traffic. To conduct urban operations, sUAS-based delivery systems must obey regulations for sUAS operations and avoid urban obstacles. In this paper, a maximum-flight-time-constrained multitrip vehicle routing problem with time windows optimization model is used to create routes for sUAS-based delivery missions. To address the actual urban environment with the optimization model, a two-layered urban flight network is built by feeding an airborne light detection and ranging sensor data into an algorithm that uses a Voronoi diagram to create collision-free paths. This paper uses this approach to study a possible package delivery using sUAS in San Diego, CA.
机译:随着用于小型无人机系统(sUAS)的新技术的出现,例如轻型传感器和高效电池,小型无人机(sUAV)的运行将从军事用途扩展到商业用途。 sUAS的一项有前途的商业应用是包裹递送,因为它具有减少最后一英里递送系统的购置和运营成本的潜力,同时可以实现诸如当天递送之类的新服务。此外,在城市地区,sUAV可以向客户交付包裹,而不会对街道交通造成负面影响。为了进行城市运营,基于sUAS的交付系统必须遵守sUAS运营的规定,并避免城市障碍。在本文中,具有时间窗优化模型的最大飞行时间约束的多程车辆路径问题被用于为基于sUAS的交付任务创建路径。为了使用优化模型解决实际的城市环境,通过将机载光检测和测距传感器数据输入到使用Voronoi图创建无碰撞路径的算法中,构建了一个两层的城市飞行网络。本文使用这种方法来研究使用位于加利福尼亚州圣地亚哥的sUAS进行的包裹递送。

著录项

  • 来源
    《Journal of Aircraft》 |2019年第6期|2309-2323|共15页
  • 作者单位

    Georgia Inst Technol Aerosp Syst Design Lab Sch Aerosp Engn 270 Ferst Dr Atlanta GA 30332 USA;

    Georgia Inst Technol Sch Aerosp Engn Adv Aerosp Syst Anal 270 Ferst Dr Atlanta GA 30332 USA|Georgia Inst Technol Aerosp Syst Design Lab 270 Ferst Dr Atlanta GA 30332 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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