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dc.contributor.authorMontero Mercadé, Lídia
dc.contributor.authorPacheco, Meritxell
dc.contributor.authorBarceló Bugeda, Jaime
dc.contributor.authorHomoceanu, Silviu
dc.contributor.authorCasanovas Garcia, Josep
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2017-05-15T08:33:43Z
dc.date.available2017-05-15T08:33:43Z
dc.date.issued2016-10-01
dc.identifier.citationLídia Montero, Pacheco, M., Barcelo, J., Homoceanu, S., Casanovas, J. Case study on cooperative car data for estimating traffic states in an urban network. "Transportation research record", 1 Octubre 2016, núm. 2594, p. 127-137.
dc.identifier.issn0361-1981
dc.identifier.urihttp://hdl.handle.net/2117/104399
dc.description.abstractThe use of floating car data as a particular case of probe vehicle data has been the object of extensive research for estimating traffic conditions, travel times, and origin-to-destination trip matrices. It is based on data collected from a GPS-equipped vehicle fleet or available cell phones. Cooperative cars with vehicle-to-vehicle and vehicle-to-infrastructure communication capabilities represent a step forward, as they also allow tracking of vehicles surrounding the equipped car. This paper presents the results of a limited experiment with a small fleet of cooperative cars in the central business district of Barcelona, Spain, known as L’Eixample District. Data collected from the experiment were used to build and calibrate the emulation of cooperative functions in a microscopic simulation model that captured the behavior of vehicle sensors in Barcelona’s central business district. Such a calibrated model allows emulating fleet data on a large scale that goes far beyond what a small fleet of cooperative vehicles could capture. To determine the traffic state, several approaches were developed for estimating traffic variables—whose accuracy depends on the penetration level of the technology—on the basis of extensions of Edie’s generalized definitions of the fundamental traffic variables with the emulated data.
dc.format.extent11 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.otherProbe vehicle
dc.subject.otherLagrangian sensing
dc.subject.otherTraffic Flow
dc.subject.otherSimulation
dc.subject.otherTraffic State Estimation
dc.subject.otherCooperative Car data
dc.titleCase study on cooperative car data for estimating traffic states in an urban network
dc.typeArticle
dc.contributor.groupUniversitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació
dc.identifier.doi10.3141/2594-16
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations
dc.relation.publisherversionhttp://trrjournalonline.trb.org/doi/abs/10.3141/2594-16
dc.rights.accessOpen Access
drac.iddocument19262002
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/PRI2014-2017/2014SGR1534
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TRA2014-52530-C3-3-P
upcommons.citation.authorMontero, Lídia; Pacheco, M.; Barcelo, J.; Homoceanu, S.; Casanovas, J.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameTransportation research record
upcommons.citation.number2594
upcommons.citation.startingPage127
upcommons.citation.endingPage137


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Llevat que s'hi indiqui el contrari, els continguts d'aquesta obra estan subjectes a la llicència de Creative Commons: Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya