A Comparative Review of Air Drones (UAVs) and Delivery Bots (SUGVs) for Automated Last Mile Home Delivery

Fang Li () and Oliver Kunze ()
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Fang Li: Institute for Logistics, Risk- and Resource Management (ILR), Neu-Ulm University of Applied Sciences, Wileystraße 1, 89231 Neu-Ulm, Germany
Oliver Kunze: Institute for Logistics, Risk- and Resource Management (ILR), Neu-Ulm University of Applied Sciences, Wileystraße 1, 89231 Neu-Ulm, Germany

Logistics, 2023, vol. 7, issue 2, 1-32

Abstract: Background : UAVs (Unmanned Aerial Vehicles) and SUGVs (Sidewalk Unmanned Ground Vehicles) are two prominent options to revolutionize last mile home delivery. However, there is no literature yet addressing a comprehensive assessment of them. To bridge this research gap, this paper aimed to compare UAVs to SUGVs in the context of urban parcel delivery from a practical, conceptual, technological, commercial, and environmental perspective. Methodology : Based on structured literature and web research, this paper provided a comparative status quo review of these two delivery concepts. We introduced a parameter-based cost calculus model to estimate the costs per shipment for each technology. To detect the key cost drivers, we applied a one-way sensitivity analysis, as well as a “full factorial design of experiment” approach. Results : These key cost drivers for both operations are the “number of vehicles per operator” and the “average beeline service radius”. From today’s commercial point of view, our model indicated better profitability of SUGVs. However, technical and regulatory developments may render different results in the future. As SUGVs emit significantly less noise than UAVs, we assume that SUGVs have an additional advantage for usage in autonomous urban last mile delivery from a resident’s perspective. Conclusions : Both key cost drivers will significantly influence the commercial viability of unmanned home delivery services. Safety and security aspects will determine regulatory rules on “number of vehicles per operator”. To increase the “average beeline service radius”, UAVs could profit from mothership delivery concepts while SUGV delivery may co-use existing public transport infrastructure.

Keywords: automated vehicles; cost analysis; delivery bots; drones; last mile delivery; noise; sidewalk unmanned ground vehicles; SUGV; unmanned aerial vehicles; UAV (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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