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Traffic management as a service: the traffic flow pattern classification problem

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Traffic management as a service: the traffic flow pattern classification problem

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dc.contributor.author Tavares de Araujo Cesariny Calafate, Carlos Miguel es_ES
dc.contributor.author Soler Fernández, David es_ES
dc.contributor.author Cano Escribá, Juan Carlos es_ES
dc.contributor.author Manzoni, Pietro es_ES
dc.date.accessioned 2016-05-23T13:47:07Z
dc.date.available 2016-05-23T13:47:07Z
dc.date.issued 2015
dc.identifier.issn 1024-123X
dc.identifier.uri http://hdl.handle.net/10251/64619
dc.description.abstract [EN] Intelligent Transportation System (ITS) technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements. es_ES
dc.description.sponsorship This work was partially supported by Valencia's Traffic Management Department and by the "Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014," Spain, under Grant TEC2014-52690-R. en_EN
dc.language Inglés es_ES
dc.publisher Hindawi Publishing Corporation es_ES
dc.relation MINECO/TEC2014-52690- R. es_ES
dc.relation.ispartof Mathematical Problems in Engineering es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Traffic management as a service: the traffic flow pattern classification problem es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1155/2015/716598
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation Tavares De Araujo Cesariny Calafate, CM.; Soler Fernández, D.; Cano Escribá, JC.; Manzoni, P. (2015). Traffic management as a service: the traffic flow pattern classification problem. Mathematical Problems in Engineering. 2015:1-14. doi:10.1155/2015/716598 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://www.hindawi.com/journals/mpe/2015/716598/ es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 14 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 2015 es_ES
dc.relation.senia 295603 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad


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