Estimation of traffic density from drone-based delivery in very low level urban airspace

无人机 大都市区 运输工程 交通拥挤 空中交通管制 订单(交换) 空中交通管理 计算机科学 工程类 业务 地理 遗传学 航空航天工程 生物 考古 财务
作者
Malik Doole,Joost Ellerbroek,Jacco Hoekstra
出处
期刊:Journal of Air Transport Management [Elsevier BV]
卷期号:88: 101862-101862 被引量:79
标识
DOI:10.1016/j.jairtraman.2020.101862
摘要

Driven by rising consumer demand, interest is growing in the application of autonomous unmanned aerial vehicles (drones) for the last-mile delivery of small express packages and fast-food meals in cities. To be realised, this would require the Very Low Level (VLL) urban airspace to be able to cope with high traffic densities of commercial delivery drones. The potential benefits of such novel drone-based applications are a reduction of traffic congestion in cities, lower greenhouse gas emissions and more efficient transportation operations. To help realise this concept, programs such as U-Space, the unmanned traffic management system for Europe, are developing important services such as deconfliction management and dynamic capacity management. However, for several of these services, design choices will depend on how, and how extensive they will be used. It therefore becomes important to estimate how many delivery drones would operate in a typical city. This paper aims to provide an estimate by establishing a framework to determine the traffic demand for express drone-based package delivery of five European countries. In addition, a detailed case-study is presented for determining traffic density of express package drone delivery for Paris metropolitan area in order to assess the feasibility from a user's perspective. The paper also discusses the potential of fast-food meal delivery drones compared to traditional delivery modes for Paris. Results suggest that hourly traffic densities culminating from express package and fast-food meal delivery drones will exceed today's global commercial aircraft traffic of 10,000 per day by more than six-fold for just one potential metropolitan city.

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