aerospace
Article
Constrained Urban Airspace Design for Large-Scale
Drone-Based Delivery Traffic
Malik Doole
1,
*, Joost Ellerbroek
1
, Victor L. Knoop
2
and Jacco M. Hoekstra
1
Citation: Doole, M.; Ellerbroek, J.;
Knoop, V.L.; Hoekstra, J.M.
Constrained Urban Airspace Design
for Large-Scale Drone-Based Delivery
Traffic. Aerospace 2021, 8, 38. https://
doi.org/10.3390/aerospace8020038
Received: 11 December 2020
Accepted: 25 January 2021
Published: 1 February 2021
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4.0/).
1
Control and Simulation, Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1,
2629 HS Delft, The Netherlands; J.Ellerbroek@tudelft.nl (J.E.); J.M.Hoekstra@tudelft.nl (J.M.H.)
2
Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology,
Stevinweg 1, 2628 CN Delft, The Netherlands; V.L.Knoop@tudelft.nl
* Correspondence: M.M.Doole@tudelft.nl
Abstract: Large-scale adoption of drone-based delivery in urban areas promise societal benefits
with respect to emissions and on-ground traffic congestion, as well as potential cost savings for
drone-based logistic companies. However, for this to materialise, the ability of accommodating high
volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained
airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict
probability. The current study investigates the application of these principles to a highly constrained
airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and
one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-
altitude rules to vertically segment cruising traffic according to their travel direction. These airspace
configurations also feature transition altitudes to accommodate turning flights that need to decrease
the flight speed in order to make safe turns at intersections. While using fast-time simulation
experiments, the performance of these airspace concepts is compared and evaluated for multiple
traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective
way to structure drone traffic in a constrained urban area is to have vertically segmented altitude
layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic.
The study also makes recommendations for areas of future research, which are aimed at supporting
dynamic traffic demand patterns.
Keywords: urban airspace design; constrained airspace; UTM; U-Space; drone delivery; urban air
mobility; smart cities
1. Introduction
The current advancement in unmanned aerial vehicles, which is commonly referred
to as drones, has potential applications in agriculture, research, inspection, health-care,
urban air mobility [1–7], and logistics, especially in the transport of small express packages
of consumer goods and fast-food meals within cities [8–11]. Recently, this demand has
been exemplified by commercial logistics companies conducting drone delivery test flights
in dense urban areas [12,13]. One reason for this interest is the potential environmental
benefit [14] and the attractive economics of drone-based delivery [15,16]. However, if the
large-scale adoption of drone-based delivery does begin to unfold, safely organising such
traffic in the low altitude urban airspace, which is highly constrained by existing street
networks and buildings, will be one of the main challenges to overcome.
In order to cope with the future demand for drone-based services, previous research,
such as the Metropolis project, has demonstrated that vertically segmenting the airspace in
order to separate cruising traffic with respect to travel directions at different altitudes, leads
to high levels of safety [17,18]. The study revealed that two factors, segmentation of traffic
and the reduction of relative velocities (i.e., alignment of traffic), between cruising traffic at
the same altitude were the main contributors to lowering the conflict probability and, thus,
Aerospace 2021, 8, 38. https://doi.org/10.3390/aerospace8020038 https://www.mdpi.com/journal/aerospace