A Deviation Flow Refueling Location Model for Continuous Space: A Commercial Drone Delivery System for Urban Areas

被引：47

作者：

Hong, Insu ^{[1
]}

Kuby, Michael ^{[2
]}

Murray, Alan ^{[3
]}

机构：

[1] West Virginia Univ, Dept Geol & Geog, 98 Beechurst Ave, Morgantown, WV 26506 USA

[2] Arizona State Univ, Sch Geog Sci & Urban Planning, Coor Hall 5515,975 S Myrtle Ave, Tempe, AZ 85287 USA

[3] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA

来源：

ADVANCES IN GEOCOMPUTATION | 2017年

关键词：

Drone; Coverage location model; Euclidean shortest path;

D O I：

10.1007/978-3-319-22786-3_12

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Drones, which refer to a range of small-sized unmanned aerial vehicles propelled by multiple rotors, recently have been utilized for various purposes, such as military, surveillance, photography, and entertainment. Delivery service for small products is one of their potential applications, and optimal path planning is essential for operational efficiency of such a delivery service. Because a drone's movement is not limited to existing transportation networks, path planning needs to be conducted in continuous space while taking into account obstacles for flight. However, due to the limited flight range of battery-powered drones, multiple recharging stations are required in large urban areas to complete delivery without running out of power. In this chapter, we present a new coverage model that can optimize the location of recharging stations for delivery drones as well as ensure construction of a feasible delivery network that connects the stations and covered demand based on continuous space shortest paths. A heuristic solution technique is utilized for the optimization of station locations. Application results show the effectiveness of our model for construction of a drone delivery network that covers a large urban area.

引用

页码：125 / 132

页数：8

共 13 条

[1] Visibility of Disjoint Polygons [J].