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dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorTajtehranifard, Hen_US
dc.creatorBhaskar, Aen_US
dc.creatorNassir, Nen_US
dc.creatorHaque, MMen_US
dc.creatorChung, Een_US
dc.date.accessioned2018-01-23T02:25:48Z-
dc.date.available2018-01-23T02:25:48Z-
dc.identifier.issn0968-090Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/71590-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2018. 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 Tajtehranifard, H., Bhaskar, A., Nassir, N., Haque, M. M., & Chung, E. (2018). A path marginal cost approximation algorithm for system optimal quasi-dynamic traffic assignment. Transportation Research Part C: Emerging Technologies, 88, 91-106 is available at https://dx.doi.org/10.1016/j.trc.2018.01.002en_US
dc.subjectQuasi-dynamic traffic assignmenten_US
dc.subjectSystem optimal traffic assignmenten_US
dc.subjectPath marginal cost approximationen_US
dc.titleA path marginal cost approximation algorithm for system optimal quasi-dynamic traffic assignmenten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage91en_US
dc.identifier.epage106en_US
dc.identifier.volume88en_US
dc.identifier.doi10.1016/j.trc.2018.01.002en_US
dcterms.abstractThis study introduces an efficient path-based System-Optimal Quasi-Dynamic Traffic Assignment (SOQDTA) framework that benefits from the computational efficiency of static traffic assignment models, yet captures the realism of traffic flow, with less complexity and a lower computational burden, compared to dynamic traffic assignment models.en_US
dcterms.abstractTo solve the proposed SOQDTA problem, we have developed a novel Path Marginal Cost (PMC) approximation algorithm, based on a Quasi-Dynamic Network Loading (QDNL) procedure (Bliemer et al., 2014), that incorporates a first order node model, and thus produces realistic path travel times consistent with queuing theory, and similar to those of dynamic network loading models, but at a lower computational cost. The model considers capacity constrained static flows, residual vertical/point queues and no spillback.en_US
dcterms.abstractThe proposed SOQDTA model is applied to the test network of Sioux Falls and is demonstrated to result in system optimal traffic flow patterns that improve total system travel times compared to the user equilibrium solution. In the case study experiment, the convergence of the algorithm is demonstrated using a relative gap function. A sensitivity analysis is performed to realize the impact of perturbation size on the solution quality, and a discussion is presented on the selection of perturbation size for general network applications.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation research. Part C, Emerging technologies, Mar. 2018, v. 88, p. 91-106en_US
dcterms.isPartOfTransportation research. Part C, Emerging technologiesen_US
dcterms.issued2018-03-
dc.description.validate201801 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0150-n01en_US
dc.description.pubStatusPublisheden_US
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