Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/101044
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorShen, Len_US
dc.creatorShao, Hen_US
dc.creatorWu, Ten_US
dc.creatorFainman, EZen_US
dc.creatorLam, WHKen_US
dc.date.accessioned2023-08-30T04:14:24Z-
dc.date.available2023-08-30T04:14:24Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/101044-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2020 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Shen, L., Shao, H., Wu, T., Fainman, E. Z., & Lam, W. H. K. (2020). Finding the reliable shortest path with correlated link travel times in signalized traffic networks under uncertainty. Transportation Research Part E: Logistics and Transportation Review, 144, 102159 is available at https://dx.doi.org/10.1016/j.tre.2020.102159.en_US
dc.subjectDelay at intersectionsen_US
dc.subjectReliabilityen_US
dc.subjectReliable path-finding algorithmen_US
dc.subjectTransportationen_US
dc.subjectTravel time correlationsen_US
dc.titleFinding the reliable shortest path with correlated link travel times in signalized traffic networks under uncertaintyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume144en_US
dc.identifier.doi10.1016/j.tre.2020.102159en_US
dcterms.abstractThis article proposes an innovative path finding algorithm to achieve on-time arrival reliability on road networks under uncertainty with stochastic delays at signalized intersections. Typically, we extend conventional path-finding algorithms to signalized traffic networks of 1) random and correlated running travel time along links (RTTL), 2) delays at intersections and traffic signals (DITS) and their correlations, as well as 3) correlations between RTTL and DITS. We first discuss the theoretical foundations concerning the existence of the optimal solutions and analyze the efficient convergence speed of our proposed algorithm. Lastly, we conduct numerical studies to demonstrate efficiency and effectiveness of the proposed algorithm.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Dec. 2020, v. 144, 102159en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2020-12-
dc.identifier.scopus2-s2.0-85097100951-
dc.identifier.eissn1878-5794en_US
dc.identifier.artn102159en_US
dc.description.validate202308 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-0622-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextTop Six Talents' Project of Jiangsu Province; National Natural Science Foundation of China; Hong Kong Polytechnic University; Xuzhou Medical University; Fundamental Research Funds for the Central Universitiesen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS40343501-
dc.description.oaCategoryGreen (AAM)en_US
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