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Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks

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  • Angelo Furno
  • Nour-Eddin El Faouzi
  • Rajesh Sharma
  • Eugenio Zimeo

Abstract

Betweenness Centrality (BC) has proven to be a fundamental metric in many domains to identify the components (nodes) of a system modelled as a graph that are mostly traversed by information flows thus being critical to the proper functioning of the system itself. In the transportation domain, the metric has been mainly adopted to discover topological bottlenecks of the physical infrastructure composed of roads or railways. The adoption of this metric to study the evolution of transportation networks that take into account also the dynamic conditions of traffic is in its infancy mainly due to the high computation time needed to compute BC in large dynamic graphs. This paper explores the adoption of dynamic BC, i.e., BC computed on dynamic large-scale graphs, modeling road networks and the related vehicular traffic, and proposes the adoption of a fast algorithm for ahead monitoring of transportation networks by computing approximated BC values under time constraints. The experimental analysis proves that, with a bounded and tolerable approximation, the algorithm computes BC on very large dynamically weighted graphs in a significantly shorter time if compared with exact computation. Moreover, since the proposed algorithm can be tuned for an ideal trade-off between performance and accuracy, our solution paves the way to quasi real-time monitoring of highly dynamic networks providing anticipated information about possible congested or vulnerable areas. Such knowledge can be exploited by travel assistance services or intelligent traffic control systems to perform informed re-routing and therefore enhance network resilience in smart cities.

Suggested Citation

  • Angelo Furno & Nour-Eddin El Faouzi & Rajesh Sharma & Eugenio Zimeo, 2021. "Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-35, March.
    • Handle: RePEc:plo:pone00:0248764
    DOI: 10.1371/journal.pone.0248764
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    References listed on IDEAS

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    1. Mariska van Essen & Tom Thomas & Eric van Berkum & Caspar Chorus, 2016. "From user equilibrium to system optimum: a literature review on the role of travel information, bounded rationality and non-selfish behaviour at the network and individual levels," Transport Reviews, Taylor & Francis Journals, vol. 36(4), pages 527-548, July.
    2. Petter Holme, 2003. "Congestion And Centrality In Traffic Flow On Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 163-176.
    3. B. Berche & C. von Ferber & T. Holovatch & Yu. Holovatch, 2009. "Resilience of public transport networks against attacks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(1), pages 125-137, September.
    4. Yihui Ren & Mária Ercsey-Ravasz & Pu Wang & Marta C. González & Zoltán Toroczkai, 2014. "Predicting commuter flows in spatial networks using a radiation model based on temporal ranges," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    5. Zhao, Shuangming & Zhao, Pengxiang & Cui, Yunfan, 2017. "A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 143-157.
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    Cited by:

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