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

  • Identification data

    Identifier: PC:4137
    Handle: https://hdl.handle.net/20.500.11797/PC4137
    Authors:
    Solé-Ribalta, Albert
    Abstract:
    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.

  • Others:

    Subject matter: Enginyeria
    Access rights: info:eu-repo/semantics/openAccess
    Researcher identifier: 0000-0002-2953-5338
    Published by (editorial): Universitat Rovira i Virgili (URV)
    Related publications: 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
    Abstract: 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.
    Departament: Enginyeria Informàtica i Matemàtiques
    DOI: 10.5061/dryad.32mq0
    Document type: info:eu-repo/semantics/other
    Related publication's DOI: 10.1098/rsos.160098
    Repository ingest date: 2016-09-09
    Author: Solé-Ribalta, Albert
    Keywords: Complex networks, congestion phenomena, critical phenomena
    Dataset publication year: 2016
    Dataset title: Data from: A model to identify urban traffic congestion hotspots in complex networks

  • Keywords:

    Enginyeria
    Complex networks, congestion phenomena, critical phenomena

  • Documents:

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