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Dynamic grouping of vehicle trajectories
[Agrupamiento dinámico de trayectorias vehiculares]

Author

Listed:
  • Reyes, Gary
  • Lanzarini, Laura
  • Estrebou, Cesar
  • Bariviera, Aurelio F.

Abstract

Vehicular traffic volume in large cities has increased in recent years, causing mobility problems; therefore,the analysis of vehicle flow data becomes a relevant research topic. Intelligent Transportation Systems monitor and control vehicular movements by collecting GPS trajectories, which provides the geographic location of vehicles in real time. Thus information is processed using clustering techniques to identify vehicular flow patterns. This work presents a methodologycapable of analyzing the vehicular flow in a given area, identifying speed ranges and keeping an interactivemap updated that facilitates the identification of possible traffic jam areas. The results obtained on threedata sets from the cities of Guayaquil-Ecuador, RomeItaly and Beijing-China are satisfactory and clearlyrepresent the speed of movement of the vehicles, automatically identifying the most representative ranges inreal time.

Suggested Citation

  • Reyes, Gary & Lanzarini, Laura & Estrebou, Cesar & Bariviera, Aurelio F., 2022. "Dynamic grouping of vehicle trajectories [Agrupamiento dinámico de trayectorias vehiculares]," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 22(2), pages 141-150.
  • Handle: RePEc:zbw:espost:268416
    DOI: 10.24215/16666038.22.e11
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    File URL: https://www.econstor.eu/bitstream/10419/268416/1/2022_Dynamic_grouping_of_vehicle_trajectories%20REYES%20LANZARINI%20ESTREBOU%20BARIVIERA.pdf
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    Cited by:

    1. Gary Reyes & Roberto Tolozano-Benites & Laura Lanzarini & César Estrebou & Aurelio F. Bariviera & Julio Barzola-Monteses, 2023. "Methodology for the Identification of Vehicle Congestion Based on Dynamic Clustering," Sustainability, MDPI, vol. 15(24), pages 1-18, December.

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