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Data from: A model to identify urban traffic congestion hotspots in complex networks

  • Datos identificativos

    Identificador: PC:4137
    Handle: https://hdl.handle.net/20.500.11797/PC4137
    Autores:
    Solé-Ribalta, Albert
    Resumen:
    The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable for improvement and control. Here, we propose an idealized model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities’ road networks, considering, in some experiments, real- traffic data, show that the proposed model is capable of identifying susceptible junctions that might becomes hotspots if mobility demand increases.

  • Otros:

    Materia: Enginyeria
    Derechos de acceso: info:eu-repo/semantics/openAccess
    Identificador del investigador: 0000-0002-2953-5338
    Publicado por (editorial): Universitat Rovira i Virgili (URV)
    Publicaciones relacionadas: Solé-Ribalta, A., Gómez, S., & Arenas, A. (2016). A model to identify urban traffic congestion hotspots in complex networks. Royal Society Open Science, 3(10), 160098. https://doi.org/10.1098/rsos.160098
    Resumen: The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable for improvement and control. Here, we propose an idealized model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities’ road networks, considering, in some experiments, real- traffic data, show that the proposed model is capable of identifying susceptible junctions that might becomes hotspots if mobility demand increases.
    Departamento: Enginyeria Informàtica i Matemàtiques
    DOI: 10.5061/dryad.32mq0
    Tipo de documento: info:eu-repo/semantics/other
    DOI de la publicación relacionada: 10.1098/rsos.160098
    Fecha alta repositorio: 2016-09-09
    Autor: Solé-Ribalta, Albert
    Palabras clave: Complex networks, congestion phenomena, critical phenomena
    Año de publicación de la dataset: 2016
    Título del conjunto de datos: Data from: A model to identify urban traffic congestion hotspots in complex networks

  • Palabras clave:

    Enginyeria
    Complex networks, congestion phenomena, critical phenomena

  • Documentos:

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