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dc.contributor.authorBarceló Bugeda, Jaime
dc.contributor.authorMontero Mercadé, Lídia
dc.contributor.authorBullejos, Manuel
dc.contributor.authorLinares Herreros, María Paz
dc.contributor.authorSerch Muni, Oriol
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.contributor.otherFacultat d'Informàtica de Barcelona
dc.date.accessioned2014-03-18T18:19:12Z
dc.date.available2014-03-18T18:19:12Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationBarcelo, J. [et al.]. Robustness and computational efficiency of a Kalman Filter estimator of time-dependent origin-destination matrices: exploiting ICT traffic measurements from information and communications technologiess. A: Transportation Research Board Annual Meeting. "Travel Demand Forecasting 2013, Volume 2". Washington: 2013, p. 31-39.
dc.identifier.isbn9780309286718
dc.identifier.urihttp://hdl.handle.net/2117/22278
dc.description.abstractOrigin–destination (O-D) trip matrices that describe the patterns of traffic behavior across a network are the primary data input used in principal traffic models and, therefore, a critical requirement in all advanced systems supported by dynamic traffic assignment models. However, because O-D matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts that are provided by an existing layout of traffic-counting stations. The availability of new traffic measurements provided by information and communication technologies (ICT) allows more efficient algorithms, namely for real-time estimation of O-D matrices that are based on modified Kalman filtering approaches to exploit the new data. The quality of the estimations depends on various factors such as the penetration of the ICT devices, the detection layout, and the quality of the initial information. The feasibility of real-time applications depends on the computational performance of the proposed algorithms for urban networks of sensitive size. This paper presents the results of a set of computational experiments with a microscopic simulation of the network of Barcelona’s central business district that explore the sensitivity of the Kalman filter estimates in relation to design factor values.
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::Simulació
dc.subject.lcshSimulation methods
dc.subject.lcshKalman filtering
dc.subject.otherDynamic OD Estimation
dc.subject.otherDynamic User Equilibrium (DUE)
dc.subject.otherTraffic Detectors Layout
dc.subject.otherKalman Filtering
dc.titleRobustness and computational efficiency of a Kalman Filter estimator of time-dependent origin-destination matrices: exploiting ICT traffic measurements from information and communications technologiess
dc.typeConference report
dc.subject.lemacKalman, Filtratge de
dc.subject.lemacSimulació, Mètodes de
dc.contributor.groupUniversitat Politècnica de Catalunya. PROMALS - Grup de Recerca en Programació Matemática, Logística i Simulació
dc.identifier.doi10.3141/2344-04
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::90 Operations research, mathematical programming::90C Mathematical programming
dc.relation.publisherversionhttp://trid.trb.org/view/2013/C/1242276
dc.rights.accessOpen Access
drac.iddocument11611653
dc.description.versionPostprint (author draft version)
upcommons.citation.authorBarcelo, J.; Montero, L.; Bullejos, M.; Linares, M.; Serch, O.
upcommons.citation.contributorTransportation Research Board Annual Meeting
upcommons.citation.pubplaceWashington
upcommons.citation.publishedtrue
upcommons.citation.publicationNameTravel Demand Forecasting 2013, Volume 2
upcommons.citation.startingPage31
upcommons.citation.endingPage39


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