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Modeling and Characterization of Traffic Flows in Urban Environments

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Modeling and Characterization of Traffic Flows in Urban Environments

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dc.contributor.author Zambrano-Martinez, Jorge es_ES
dc.contributor.author Tavares De Araujo Cesariny Calafate, Carlos Miguel es_ES
dc.contributor.author Soler Fernández, David es_ES
dc.contributor.author Cano, Juan-Carlos es_ES
dc.contributor.author Manzoni, Pietro es_ES
dc.date.accessioned 2019-05-29T20:42:22Z
dc.date.available 2019-05-29T20:42:22Z
dc.date.issued 2018 es_ES
dc.identifier.uri http://hdl.handle.net/10251/121259
dc.description.abstract [EN] Currently, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic by predicting future traffic conditions for optimizing the route of automated vehicles, and if these measures could be taken to preventively mitigate the effects of congestion with its related problems, the overall traffic flow could be improved. This paper performs an experimental study of the traffic distribution in the city of Valencia, Spain, characterizing the different streets of the city in terms of vehicle load with respect to the travel time during rush hour traffic conditions. Experimental results based on realistic vehicular traffic traces from the city of Valencia show that only some street segments fall under the general theory of vehicular flow, offering a good fit using quadratic regression, while a great number of street segments fall under other categories. Although in some cases such discrepancies are related to lack of traffic, injecting additional vehicles shows that significant mismatches still persist. Thus, in this paper we propose an equation to characterize travel times over a segment belonging to the sigmoid family; specifically, we apply logistic regression, being able to significantly improve the curve fitting results for most of the street segments under analysis. Based on our regression results, we performed a clustering analysis of the different street segments, showing that they can be classified into three well-defined categories, which evidences a predictable traffic distribution using the logistic regression throughout the city during rush hours, and allows optimizing the traffic for automated vehicles. es_ES
dc.description.sponsorship This work was partially supported by Valencia's Traffic Management Department, 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, and the "Programa de Becas SENESCYT" de la Republica del Ecuador. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation MINECO/TEC2014-52690-R-AR es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Autonomous vehicles es_ES
dc.subject Intelligent transportation systems es_ES
dc.subject SUMO es_ES
dc.subject DFROUTER es_ES
dc.subject Traffic prediction es_ES
dc.subject Traffic behavior es_ES
dc.subject Logistic regression es_ES
dc.subject Clustering es_ES
dc.subject Urban traffic es_ES
dc.subject Valencia es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Modeling and Characterization of Traffic Flows in Urban Environments es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s18072020 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada 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.description.bibliographicCitation Zambrano-Martinez, J.; Tavares De Araujo Cesariny Calafate, CM.; Soler Fernández, D.; Cano, J.; Manzoni, P. (2018). Modeling and Characterization of Traffic Flows in Urban Environments. Sensors. 18(7):1-19. https://doi.org/10.3390/s18072020 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.3390/s18072020 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 18 es_ES
dc.description.issue 7 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 29937507
dc.identifier.pmcid PMC6068873
dc.relation.pasarela 364771 es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES


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