Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98054
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorCheng, Zen_US
dc.creatorYao, Jen_US
dc.creatorChen, Aen_US
dc.creatorAn, Sen_US
dc.date.accessioned2023-04-06T07:55:53Z-
dc.date.available2023-04-06T07:55:53Z-
dc.identifier.issn2324-9935en_US
dc.identifier.urihttp://hdl.handle.net/10397/98054-
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rights© 2021 Hong Kong Society for Transportation Studies Limiteden_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica A: Transport Science on 19 Jul 2021 (Published online), available at: http://www.tandfonline.com/10.1080/23249935.2021.1953189.en_US
dc.subjectParadox conditionen_US
dc.subjectRoute choiceen_US
dc.subjectStochastic traffic assignmenten_US
dc.subjectTraffic paradoxen_US
dc.subjectTransportationen_US
dc.titleAnalysis of a multiplicative hybrid route choice model in stochastic assignment paradoxen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1544en_US
dc.identifier.epage1568en_US
dc.identifier.volume18en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1080/23249935.2021.1953189en_US
dcterms.abstractIn recent years, a multiplicative hybrid (MH) route choice model was proposed to overcome the drawbacks of the multinomial logit (MNL) model and the multinomial weibit (MNW) model. This paper compares the conditions for the stochastic traffic assignment paradox of the three models. We analyze the condition when improving a link in an uncongested network counterintuitively increases total travel costs. Using three typical flow-independent networks (two links, (Formula presented.) independent links, and (Formula presented.) routes with (Formula presented.) overlapping links), we reveal the strong relationships in the paradox conditions of the three models. We further study the paradoxical features of the three models in the Sioux-Falls network, where the model parameters are estimated from simulated route sets. The case study shows that (1) the MH model fits the data the best, (2) using the MNL or the MNW model to identify paradox links exhibits intrinsic tendencies that are consistent with the theoretical analysis, and (3) the paradox links identified by the MH model is a compromise of the other two models. This paper delves into the relationships of the three models in the stochastic assignment paradox and provides suggestions and caveats to the application of the three models.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportmetrica. A, Transport science, 2022, v. 18, no. 3, p. 1544-1568en_US
dcterms.isPartOfTransportmetrica. A, Transport scienceen_US
dcterms.issued2022-
dc.identifier.scopus2-s2.0-85110854020-
dc.identifier.eissn2324-9943en_US
dc.description.validate202303 bcfcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-0504-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNatural Science Foundation of China; China Postdoctoral Science Foundation; International Postdoctoral Exchange Fellowship of China Postdoctoral Council; Research Committee of the Hong Kong Polytechnic University; CCF-DiDi Big Data Joint Laben_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS54128493-
dc.description.oaCategoryGreen (AAM)en_US
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