Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96005
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorHänseler, FSen_US
dc.creatorLam, WHKen_US
dc.creatorBierlaire, Men_US
dc.creatorLederrey, Gen_US
dc.creatorNikolić, Men_US
dc.date.accessioned2022-11-01T03:38:35Z-
dc.date.available2022-11-01T03:38:35Z-
dc.identifier.issn0191-2615en_US
dc.identifier.urihttp://hdl.handle.net/10397/96005-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2016 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Hänseler, F. S., Lam, W. H. K., Bierlaire, M., Lederrey, G., & Nikolić, M. (2017). A dynamic network loading model for anisotropic and congested pedestrian flows. Transportation Research Part B: Methodological, 95, 149-168 is available at https://doi.org/10.1016/j.trb.2016.10.017.en_US
dc.subjectAnisotropyen_US
dc.subjectCalibrationen_US
dc.subjectMacroscopic modelen_US
dc.subjectNetwork loadingen_US
dc.subjectPedestrian flowen_US
dc.subjectPedestrian fundamental diagramen_US
dc.titleA dynamic network loading model for anisotropic and congested pedestrian flowsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage149en_US
dc.identifier.epage168en_US
dc.identifier.volume95en_US
dc.identifier.doi10.1016/j.trb.2016.10.017en_US
dcterms.abstractA macroscopic loading model for multi-directional, time-varying and congested pedestrian flows is proposed. Walkable space is represented by a network of streams that are each associated with an area in which they interact. To describe this interaction, a stream-based pedestrian fundamental diagram is used that relates density and walking speed in multi-directional flow. The proposed model is applied to two different case studies. The explicit modeling of anisotropy in walking speed is shown to significantly improve the ability of the model to reproduce empirically observed walking time distributions. Moreover, the obtained model parametrization is in excellent agreement with the literature.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation research. Part B, Methodological, Jan. 2017, v. 95, p. 149-168en_US
dcterms.isPartOfTransportation research. Part B, Methodologicalen_US
dcterms.issued2017-01-
dc.identifier.scopus2-s2.0-85006905674-
dc.identifier.eissn1879-2367en_US
dc.description.validate202211 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-2271-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6707482-
dc.description.oaCategoryGreen (AAM)en_US
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