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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.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.relation.projectID | info:eu-repo/grantAgreement/MINECO//TEC2014-52690-R/ES/INTEGRACION DEL SMARTPHONE Y EL VEHICULO PARA CONECTAR CONDUCTORES, SENSORES Y ENTORNO A TRAVES DE UNA ARQUITECTURA DE SERVICIOS FUNCIONALES/ | es_ES |
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. https://doi.org/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 |