Vehicular Flow Analysis Using Clusters

Autores
Reyes, Gary; Lanzarini, Laura Cristina; Estrebou, César Armando; Maquilón, Víctor
Año de publicación
2021
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The volume of vehicular traffic in large cities has increased in recent years, causing mobility problems, which is why the analysis of vehicular flow data becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, information that provides real-time geographic location of vehicles, which allows the identification of patterns on vehicle flow using clustering techniques. This paper presents a methodology capable of analyzing vehicular flow in a given area, identifying speed ranges and maintaining an updated interactive map that facilitates the identification of areas of possible traffic jams. The results obtained on a dataset from the city of Guayaquil-Ecuador are satisfactory and clearly represent the speed of vehicle displacement by automatically identifying the most representative ranges for each instant of time.
Workshop: WBDMD - Base de Datos y Minería de Datos
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Vehicular flow
Cluster
GPS trajectory
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/130341
Acceder
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spelling Vehicular Flow Analysis Using ClustersReyes, GaryLanzarini, Laura CristinaEstrebou, César ArmandoMaquilón, VíctorCiencias InformáticasVehicular flowClusterGPS trajectoryThe volume of vehicular traffic in large cities has increased in recent years, causing mobility problems, which is why the analysis of vehicular flow data becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, information that provides real-time geographic location of vehicles, which allows the identification of patterns on vehicle flow using clustering techniques. This paper presents a methodology capable of analyzing vehicular flow in a given area, identifying speed ranges and maintaining an updated interactive map that facilitates the identification of areas of possible traffic jams. The results obtained on a dataset from the city of Guayaquil-Ecuador are satisfactory and clearly represent the speed of vehicle displacement by automatically identifying the most representative ranges for each instant of time.Workshop: WBDMD - Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática2021-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf261-270http://sedici.unlp.edu.ar/handle/10915/130341enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4info:eu-repo/semantics/reference/hdl/10915/129809info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:47Zoai:sedici.unlp.edu.ar:10915/130341Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:47.94SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Vehicular Flow Analysis Using Clusters
title Vehicular Flow Analysis Using Clusters
spellingShingle Vehicular Flow Analysis Using Clusters
Reyes, Gary
Ciencias Informáticas
Vehicular flow
Cluster
GPS trajectory
title_short Vehicular Flow Analysis Using Clusters
title_full Vehicular Flow Analysis Using Clusters
title_fullStr Vehicular Flow Analysis Using Clusters
title_full_unstemmed Vehicular Flow Analysis Using Clusters
title_sort Vehicular Flow Analysis Using Clusters
dc.creator.none.fl_str_mv Reyes, Gary
Lanzarini, Laura Cristina
Estrebou, César Armando
Maquilón, Víctor
author Reyes, Gary
author_facet Reyes, Gary
Lanzarini, Laura Cristina
Estrebou, César Armando
Maquilón, Víctor
author_role author
author2 Lanzarini, Laura Cristina
Estrebou, César Armando
Maquilón, Víctor
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Vehicular flow
Cluster
GPS trajectory
topic Ciencias Informáticas
Vehicular flow
Cluster
GPS trajectory
dc.description.none.fl_txt_mv The volume of vehicular traffic in large cities has increased in recent years, causing mobility problems, which is why the analysis of vehicular flow data becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, information that provides real-time geographic location of vehicles, which allows the identification of patterns on vehicle flow using clustering techniques. This paper presents a methodology capable of analyzing vehicular flow in a given area, identifying speed ranges and maintaining an updated interactive map that facilitates the identification of areas of possible traffic jams. The results obtained on a dataset from the city of Guayaquil-Ecuador are satisfactory and clearly represent the speed of vehicle displacement by automatically identifying the most representative ranges for each instant of time.
Workshop: WBDMD - Base de Datos y Minería de Datos
Red de Universidades con Carreras en Informática
description The volume of vehicular traffic in large cities has increased in recent years, causing mobility problems, which is why the analysis of vehicular flow data becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, information that provides real-time geographic location of vehicles, which allows the identification of patterns on vehicle flow using clustering techniques. This paper presents a methodology capable of analyzing vehicular flow in a given area, identifying speed ranges and maintaining an updated interactive map that facilitates the identification of areas of possible traffic jams. The results obtained on a dataset from the city of Guayaquil-Ecuador are satisfactory and clearly represent the speed of vehicle displacement by automatically identifying the most representative ranges for each instant of time.
publishDate 2021
dc.date.none.fl_str_mv 2021-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/130341
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4
info:eu-repo/semantics/reference/hdl/10915/129809
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
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dc.format.none.fl_str_mv application/pdf
261-270
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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