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dc.contributor.authorMontero Mercadé, Lídia
dc.contributor.authorBarceló Bugeda, Jaime
dc.contributor.authorCodina Sancho, Esteve
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2013-02-13T17:28:22Z
dc.date.available2013-02-13T17:28:22Z
dc.date.created2012
dc.date.issued2012
dc.identifier.citationMontero, L.; Barcelo, J.; Codina, E. Adapting a dynamic OD matrix estimation approach for private traffic based on bluetooth data to passenger OD matrices. A: International Conference on Engineering and Applied Science. "2012 ICEAS: 2012 International Conference on Engineering and Applied Science: 2012 GEBF & ISSTEP: 2012 Annual Conference on Global Economy, Business and Finance: 2012 International Symposium on Society, Technology, Education and Politics: Beijin, China 2012". Beijing: 2012, p. 41-49.
dc.identifier.urihttp://hdl.handle.net/2117/17737
dc.description.abstractThe primary data input used in principal traffic models comes from Origin-Destination (OD) trip matrices, which describe the patterns of commuters across the network. In this way, OD matrices become a critical requirement in Advanced Transport Control and Management and/or Information Systems that are supported by Dynamic Traffic Assignment models (DTA models). Dynamic Transit Assignment models are a research topic, but once a dynamic transit assignment be available to practitioners, the problem of estimating the time-dependent number of trips between transportation zones shall be a critical aspect for real applications. However, OD matrices are not directly observable, neither for private nor public transport, and the current practice consists on adjusting an initial or seed matrix from link/segment counts which are provided by counting stations or data gathering in the field (detection layout). The emerging Information and Communication Technologies, especially those based on the detection of the electronic signature of on-board devices provide a rich source of data that can be used in space-state models for dynamic matrix estimation. We present a linear Kalman filter approach that makes use of counts of passengers and travel times provided by Bluetooth devices to simplify an underlying space-state model. The formulation for dynamic passenger OD matrix estimation proposed was originally developed for auto trip matrices, but in this paper, we explore the possibility of adapting the approach to the estimation of OD matrices in public transport networks.
dc.format.extent9 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització
dc.subject.lcshOperations research -- Management science
dc.subject.otherLuz/febrer/2012: Applied Science
dc.subject.otherInformation Systems
dc.subject.otherAdvanced traffic management
dc.subject.otherKalman Filtering
dc.titleAdapting a dynamic OD matrix estimation approach for private traffic based on bluetooth data to passenger OD matrices
dc.typeConference report
dc.subject.lemacInvestigació operativa ; Administració--Models matemàtics
dc.contributor.groupUniversitat Politècnica de Catalunya. PROMALS - Grup de Recerca en Programació Matemática, Logística i Simulació
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::90 Operations research, mathematical programming::90B Operations research and management science
dc.relation.publisherversionhttp://cataleg.upc.edu/record=b1419743~S1*cat
dc.rights.accessOpen Access
drac.iddocument10964837
dc.description.versionPostprint (author’s final draft)
upcommons.citation.authorMontero, L.; Barcelo, J.; Codina, E.
upcommons.citation.contributorInternational Conference on Engineering and Applied Science
upcommons.citation.pubplaceBeijing
upcommons.citation.publishedtrue
upcommons.citation.publicationName2012 ICEAS: 2012 International Conference on Engineering and Applied Science: 2012 GEBF & ISSTEP: 2012 Annual Conference on Global Economy, Business and Finance: 2012 International Symposium on Society, Technology, Education and Politics: Beijin, China 2012
upcommons.citation.startingPage41
upcommons.citation.endingPage49


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