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dc.contributor.authorLópez, David
dc.contributor.authorLozano, Angélica
dc.date.accessioned2022-09-23T07:12:36Z
dc.date.available2022-09-23T07:12:36Z
dc.date.issued2021-07
dc.identifier.isbn978-84-18465-12-3
dc.identifier.urihttp://hdl.handle.net/10259/7046
dc.descriptionTrabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgoses
dc.description.abstractIn rush hours, the onboard crowd level within transit vehicles is a problem of any large city. At the expense of time savings, some users will avoid riding crowded lines if they consider that transit vehicles do not have enough personal space. This paper presents a hypergraph model and an algorithm to find multimodal shortest hyperpaths considering the user constraints on the sequence of boarded modes and their preferences of onboard crowding levels. It is assumed that transit inter-arrivals are random. A penalty for riding transit vehicles is defined to model how the users perceive the onboard crowd levels. This penalty depends on the onboard crowd levels and the seating capacity of the vehicles. A stateautomaton is used to model the user constraints on the sequence of boarded modes. To find the shortest hyperpaths, the user selects their origin, destination, the maximum number of modal transfers, and the onboard crowd level threshold. A use case on a sample multimodal network is presented.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherUniversidad de Burgos. Servicio de Publicaciones e Imagen Institucionales
dc.relation.ispartofR-Evolucionando el transportees
dc.relation.urihttp://hdl.handle.net/10259/6490
dc.subjectTráficoes
dc.subjectTrafficen
dc.subjectTransporte públicoes
dc.subjectPublic transporten
dc.subjectLogísticaes
dc.subjectLogisticsen
dc.subject.otherIngeniería civiles
dc.subject.otherCivil engineeringen
dc.subject.otherTransportees
dc.subject.otherTransportationen
dc.titleMultimodal shortest hyperpaths considering crowding in transit vehiclesen
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.36443/9788418465123es
dc.identifier.doi10.36443/10259/7046
dc.page.initial3335es
dc.page.final3353es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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