Vehicular Flow Analysis Using Clusters

dc.creatorReyes, Gary
dc.creatorLanzarini, Laura Cristina
dc.creatorEstrebou, César Armando
dc.creatorMaquilón, Víctor
dc.date2021-10
dc.date2021
dc.date2022-02-02T17:29:43Z
dc.date.accessioned2023-07-15T05:22:15Z
dc.date.available2023-07-15T05:22:15Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/130341
dc.identifierisbn:978-987-633-574-4
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7473107
dc.descriptionThe 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.
dc.descriptionWorkshop: WBDMD - Base de Datos y Minería de Datos
dc.descriptionRed de Universidades con Carreras en Informática
dc.formatapplication/pdf
dc.format261-270
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Informáticas
dc.subjectVehicular flow
dc.subjectCluster
dc.subjectGPS trajectory
dc.titleVehicular Flow Analysis Using Clusters
dc.typeObjeto de conferencia
dc.typeObjeto de conferencia


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