Park and parcel : an agent-based exploration of last-mile freight delivery behavior as it relates to parking

Wise, Sarah and Cheliotis, Kostas and Bates, Oliver and McLeod, Fraser and Cherrett, Tom and Allen, Julian and Piecyk, Maja and Bektas, Tolga (2019) Park and parcel : an agent-based exploration of last-mile freight delivery behavior as it relates to parking. In: 2019 Spring Simulation Conference (SpringSim) :. IEEE. ISBN 9781728135472

[thumbnail of scs19paper]
Text (scs19paper)
scs19paper.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (7MB)

Abstract

Light goods vehicles are an important part of London traffic. With changes to delivery demand and traffic patterns more broadly, they often have a disproportionate impact on the functioning of cities. We partnered with industrial organizations specializing in last-mile parcel delivery, thereby gaining access to data which allowed us to construct an agent-based model of the last-mile delivery process. In this work, we expand upon the existing model to incorporate parking behavior, an important factor of delivery driving which is often overlooked in the literature. The tool we present can be used to explore different policy and infrastructure interventions.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Subjects:
?? agent-based modelingfreightlast mileparcel deliveryparkingautonomous agentssimulation platformagent-based modeldelivery processfreight deliveriesindustrial organizationinfrastructure interventionscomputational methods ??
ID Code:
135791
Deposited By:
Deposited On:
09 Oct 2019 07:50
Refereed?:
Yes
Published?:
Published
Last Modified:
26 Oct 2024 00:45