Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/97626
DC FieldValueLanguage
dc.contributorDepartment of Aeronautical and Aviation Engineeringen_US
dc.creatorZhang, Xen_US
dc.creatorLiu, Wen_US
dc.creatorLevin, Men_US
dc.creatorTravis Waller, Sen_US
dc.date.accessioned2023-03-09T03:01:29Z-
dc.date.available2023-03-09T03:01:29Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/97626-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.subjectAutonomous vehiclesen_US
dc.subjectMorning commuteen_US
dc.subjectSpatial capacity allocationen_US
dc.subjectBottleneck modelen_US
dc.subjectUser equilibriumen_US
dc.subjectSystem optimumen_US
dc.titleEquilibrium analysis of morning commuting and parking under spatial capacity allocation in the autonomous vehicle environmenten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume172en_US
dc.identifier.doi10.1016/j.tre.2023.103071en_US
dcterms.abstractThis 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.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Apr. 2023, v. 172, 103071en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2023-04-
dc.identifier.eissn1878-5794en_US
dc.identifier.artn103071en_US
dc.description.validate202303 bcwwen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera1951-
dc.identifier.SubFormID46200-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Australian Research Councilen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2026-04-30en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2026-04-30
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