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dc.contributor.authorBarceló Bugeda, Jaime
dc.contributor.authorMontero Mercadé, Lídia
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2015-12-16T18:15:58Z
dc.date.available2015-12-16T18:15:58Z
dc.date.issued2015-05-19
dc.identifier.citationBarcelo, J., Lídia Montero. "Computational framework for the estimation of dynamic OD trip matrices". 2015.
dc.identifier.urihttp://hdl.handle.net/2117/80834
dc.descriptionOrigin-Destination (OD) trip matrices describe traffic behavior patterns across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, in traffic assignment models, static or dynamic. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial a priori matrix from link flow counts, speeds, travel times and other aggregate demand data, supplied by a layout of traffic counting stations. The availability of new traffic measurements from ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications. This work proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator, whose sensitivity with respect to the available traffic measurements is analyzed.
dc.description.abstractOrigin-Destination (OD) trip matrices describe traffic behavior patterns across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, in traffic assignment models, static or dynamic. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial a priori matrix from link flow counts, speeds, travel times and other aggregate demand data, supplied by a layout of traffic counting stations. The availability of new traffic measurements from ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications; whose efficiency depends, among other factors, on the quality of the seed matrix. This paper proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator, whose sensitivity with respect to the available traffic measurements is analyzed.
dc.format.extent21 p.
dc.language.isoeng
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.otherDynamic OD Matrices
dc.subject.otherMatrix Estimation
dc.subject.otherBi-level Optimization
dc.subject.otherKalman filtering
dc.subject.otherICT data
dc.titleComputational framework for the estimation of dynamic OD trip matrices
dc.typeExternal research report
dc.contributor.groupUniversitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació
dc.rights.accessOpen Access
drac.iddocument15644624
dc.description.versionPreprint
upcommons.citation.authorBarcelo, J., Lídia Montero
upcommons.citation.publishedtrue


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