Modeling and Characterization of Traffic Flows in Urban Environments

[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...

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Autores: Zambrano-Martinez, Jorge, Soler Fernández, David, Tavares De Araujo Cesariny Calafate, Carlos Miguel|||0000-0001-5729-3041, Cano, Juan-Carlos|||0000-0002-0038-0539, Manzoni, Pietro|||0000-0003-3753-0403
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/121259
Acceso en línea:https://riunet.upv.es/handle/10251/121259
Access Level:acceso abierto
Palabra clave:Autonomous vehicles
Intelligent transportation systems
SUMO
DFROUTER
Traffic prediction
Traffic behavior
Logistic regression
Clustering
Urban traffic
Valencia
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
MATEMATICA APLICADA
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spelling Modeling and Characterization of Traffic Flows in Urban EnvironmentsZambrano-Martinez, JorgeSoler Fernández, DavidTavares De Araujo Cesariny Calafate, Carlos Miguel|||0000-0001-5729-3041Cano, Juan-Carlos|||0000-0002-0038-0539Manzoni, Pietro|||0000-0003-3753-0403Autonomous vehiclesIntelligent transportation systemsSUMODFROUTERTraffic predictionTraffic behaviorLogistic regressionClusteringUrban trafficValenciaARQUITECTURA Y TECNOLOGIA DE COMPUTADORESMATEMATICA APLICADA[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.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.MDPI AGDepartamento de Informática de Sistemas y ComputadoresEscuela Técnica Superior de Ingeniería InformáticaGrupo de Redes de ComputadoresMinisterio de Economía, Industria y CompetitividadRepositorio Institucional de la Universitat Politècnica de València Riunet20182018-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/121259reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TEC2014-52690-R INTEGRACION DEL SMARTPHONE Y EL VEHICULO PARA CONECTAR CONDUCTORES, SENSORES Y ENTORNO A TRAVES DE UNA ARQUITECTURA DE SERVICIOS FUNCIONALESopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1212592026-06-13T07:49:27Z
dc.title.none.fl_str_mv Modeling and Characterization of Traffic Flows in Urban Environments
title Modeling and Characterization of Traffic Flows in Urban Environments
spellingShingle Modeling and Characterization of Traffic Flows in Urban Environments
Zambrano-Martinez, Jorge
Autonomous vehicles
Intelligent transportation systems
SUMO
DFROUTER
Traffic prediction
Traffic behavior
Logistic regression
Clustering
Urban traffic
Valencia
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
MATEMATICA APLICADA
title_short Modeling and Characterization of Traffic Flows in Urban Environments
title_full Modeling and Characterization of Traffic Flows in Urban Environments
title_fullStr Modeling and Characterization of Traffic Flows in Urban Environments
title_full_unstemmed Modeling and Characterization of Traffic Flows in Urban Environments
title_sort Modeling and Characterization of Traffic Flows in Urban Environments
dc.creator.none.fl_str_mv Zambrano-Martinez, Jorge
Soler Fernández, David
Tavares De Araujo Cesariny Calafate, Carlos Miguel|||0000-0001-5729-3041
Cano, Juan-Carlos|||0000-0002-0038-0539
Manzoni, Pietro|||0000-0003-3753-0403
author Zambrano-Martinez, Jorge
author_facet Zambrano-Martinez, Jorge
Soler Fernández, David
Tavares De Araujo Cesariny Calafate, Carlos Miguel|||0000-0001-5729-3041
Cano, Juan-Carlos|||0000-0002-0038-0539
Manzoni, Pietro|||0000-0003-3753-0403
author_role author
author2 Soler Fernández, David
Tavares De Araujo Cesariny Calafate, Carlos Miguel|||0000-0001-5729-3041
Cano, Juan-Carlos|||0000-0002-0038-0539
Manzoni, Pietro|||0000-0003-3753-0403
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Informática de Sistemas y Computadores
Escuela Técnica Superior de Ingeniería Informática
Grupo de Redes de Computadores
Ministerio de Economía, Industria y Competitividad
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Autonomous vehicles
Intelligent transportation systems
SUMO
DFROUTER
Traffic prediction
Traffic behavior
Logistic regression
Clustering
Urban traffic
Valencia
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
MATEMATICA APLICADA
topic Autonomous vehicles
Intelligent transportation systems
SUMO
DFROUTER
Traffic prediction
Traffic behavior
Logistic regression
Clustering
Urban traffic
Valencia
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
MATEMATICA APLICADA
description [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.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/121259
url https://riunet.upv.es/handle/10251/121259
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TEC2014-52690-R INTEGRACION DEL SMARTPHONE Y EL VEHICULO PARA CONECTAR CONDUCTORES, SENSORES Y ENTORNO A TRAVES DE UNA ARQUITECTURA DE SERVICIOS FUNCIONALES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI AG
publisher.none.fl_str_mv MDPI AG
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869424109465632769
score 15.301603

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