Dynamic grouping of vehicle trajectories





Dynamic clustering, data stream, vehicular trajectories


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 methodology
capable of analyzing the vehicular flow in a given area, identifying speed ranges and keeping an interactive
map updated that facilitates the identification of possible traffic jam areas. The results obtained on three
data sets from the cities of Guayaquil-Ecuador, RomeItaly and Beijing-China are satisfactory and clearly
represent the speed of movement of the vehicles, automatically identifying the most representative ranges in
real time.


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How to Cite

Reyes, G., Lanzarini, L., Estrebou, C., & Fernandez Bariviera, A. (2022). Dynamic grouping of vehicle trajectories. Journal of Computer Science and Technology, 22(2), e11. https://doi.org/10.24215/16666038.22.e11



Original Articles