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Land efficient mobility: Evaluation of autonomous last mile delivery concepts in London

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journal contribution
posted on 2022-09-29, 13:37 authored by Maren Schnieder, Christopher Hinde, Andrew WestAndrew West
Land efficient last mile delivery concepts are key to reducing the traffic in cities and to minimising its environmental impact. This paper proposes a decision support method that evaluates the autonomous delivery concept and applies it to one year's worth of real parcel delivery data in London. Deliveries to modular and fixed lockers with autonomous delivery vans and road-based autonomous lockers (RAL) and sidewalk autonomous delivery robots (SADRs) have been simulated. Various types of autonomous delivery van fleets, depot locations, customer modes of transport, parcel demand levels, parcel locker network densities and adjustment frequencies of modular lockers are considered. A routing and scheduling algorithm is used to optimise delivery tours and vehicle choice. The optimisation algorithm finds both the optimal number of collection and delivery points (CDPs) and the delivery concept (e.g., modular lockers, sidewalk autonomous delivery robot) depending on the customer mode chosen. The results show that modular lockers which are adjusted weekly are the best option for the current or higher parcel demand levels and road-autonomous parcel lockers (RAL-R) are the best option at the lowest parcel demand level.

Funding

EPSRC Centre for Doctoral Training in Embedded Intelligence

Engineering and Physical Sciences Research Council

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History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

International Journal of Environmental Research and Public Health

Volume

19

Issue

16

Publisher

MDPI

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This article is an Open Access article published by MDPI and distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).

Acceptance date

2022-08-11

Publication date

2022-08-18

Copyright date

2022

ISSN

1661-7827

eISSN

1660-4601

Language

  • en

Depositor

Maren Schnieder. Deposit date: 29 September 2022

Article number

10290

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