Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/97626
Title: Equilibrium analysis of morning commuting and parking under spatial capacity allocation in the autonomous vehicle environment
Authors: Zhang, X
Liu, W 
Levin, M
Travis Waller, S
Issue Date: Apr-2023
Source: Transportation research. Part E, Logistics and transportation review, Apr. 2023, v. 172, 103071
Abstract: This study analytically investigates the morning commuting and parking patterns of autonomous vehicles (AVs) under different spatial road capacity allocation schemes (i.e., capacity split between inbound and outbound travel directions). Given that self-driving AV might park far away from commuters’ destination, we investigate equilibrium departure/arrival and parking patterns for AVs subject to the spatial road capacity allocation. We also analyse the system optimum traffic pattern for AV morning commute under a given capacity allocation scheme. Furthermore, we examine optimal capacity allocation strategies under user equilibrium and system optimum AV traffic patterns, respectively, which aim to minimise the total system travel cost. Numerical studies are conducted to illustrate the model and analysis. The results reveal the sensitivity of different efficiency metrics with respect to AV parking supply and road capacity allocation schemes, and provide insights into the infrastructure management with future automated transport.
Keywords: Autonomous vehicles
Morning commute
Spatial capacity allocation
Bottleneck model
User equilibrium
System optimum
Publisher: Pergamon Press
Journal: Transportation research. Part E, Logistics and transportation review 
ISSN: 1366-5545
EISSN: 1878-5794
DOI: 10.1016/j.tre.2023.103071
Appears in Collections:Journal/Magazine Article

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