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UAV Scheduling Strategies in Multi-modal Last-Mile Urban Parcel Delivery

Paper ID

ATM-2023-070

Conference

USA/Europe ATM R&D Seminar

Year

2023

Theme

Autonomous, unmanned and remotely piloted aircraft systems

Project Name

Keywords:

Continuous Approximations (CAs), multi-echelon network, Multi-modal delivery, Unmanned Aircraft Vehicles (UAVs)

Authors

Ang Li, Mark Hansen and Bo Zou

DOI

Project Number

Abstract

Urban parcel delivery has emerged as a high growth market, and the resulting delivery traffic can pose great challenges in dense urban areas. There is growing interest in supplanting the conventional model of a dedicated delivery person operating a van to alternatives featuring new classes of vehicles such as drones, autonomous ground vehicles, cargo bikes and non-motorized vehicles. This work proposes combined delivery strategies using trucks, cargo bikes and drones. We develop and compare multi-modal delivery strategies with various mode combinations. We work on zone-based multi-modal delivery strategies in multi-echelon networks. Then, we evaluate the benefit of multi-modal delivery in both uncongested and congested transportation networks. Results show that delivery models with multiple vehicles modes in both single- and multi- echelon networks are more efficient in terms of total delivery cost than truck only scenario. The multi- modal delivery strategies in two- echelon networks outperform other strategies in extremely congested situations. We suggest taking advantage of synergistic operation among emerging vehicle types, especially drones for more efficient parcel delivery.