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Vulnerability analysis for large-scale and congested road networks with demand uncertainty

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  • Chen, Bi Yu
  • Lam, William H.K.
  • Sumalee, Agachai
  • Li, Qingquan
  • Li, Zhi-Chun
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    Abstract

    To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 46 (2012)
    Issue (Month): 3 ()
    Pages: 501-516

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    Handle: RePEc:eee:transa:v:46:y:2012:i:3:p:501-516

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    Related research

    Keywords: Vulnerability analysis; Vulnerability index; Large-scale and congested road network; Reliability-based traffic assignment;

    References

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    1. Siu, Barbara W.Y. & Lo, Hong K., 2008. "Doubly uncertain transportation network: Degradable capacity and stochastic demand," European Journal of Operational Research, Elsevier, vol. 191(1), pages 166-181, November.
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    4. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
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    6. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    7. Lam, William H.K. & Shao, Hu & Sumalee, Agachai, 2008. "Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 890-910, December.
    8. Bie, Jing & Lo, Hong K., 2010. "Stability and attraction domains of traffic equilibria in a day-to-day dynamical system formulation," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 90-107, January.
    9. Wu, Xing & (Marco) Nie, Yu, 2011. "Modeling heterogeneous risk-taking behavior in route choice: A stochastic dominance approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 896-915, November.
    10. Lo, Hong K. & Luo, X.W. & Siu, Barbara W.Y., 2006. "Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 792-806, November.
    11. Chen, Anthony & Lee, Der-Horng & Jayakrishnan, R., 2002. "Computational study of state-of-the-art path-based traffic assignment algorithms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(6), pages 509-518.
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