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Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks

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Author Info

  • Anthony Chen

    ()

  • Chao Yang
  • Sirisak Kongsomsaksakul
  • Ming Lee
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    Abstract

    Accessibility is a fundamental concept in transportation analysis and urban planning. Typically, accessibility refers to the ‘ease’ of reaching opportunities for activities and services and can be used to assess the performance of a transportation and urban system. In this paper, we present network-based accessibility measures for assessing vulnerability of degradable transportation networks. The network-based accessibility measures consider the consequence of one or more link failures in terms of network travel time or generalized travel cost increase as well as the behavioral responses of users due to the failure in the network. To model different dimensions of travel behavioral responses, a combined travel demand model is adopted to estimate the long-term equilibrium network condition due to network disruptions. Numerical examples are conducted to demonstrate the feasibility of the proposed vulnerability measures for assessing degradable transportation networks. The results indicate that the accessibility measures derived from the combined travel demand model are capable of measuring the consequences of both demand and supply changes in the network and have the flexibility to reflect the effects of different travel choice dimensions on the network vulnerability. Copyright Springer Science+Business Media, LLC 2007

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    File URL: http://hdl.handle.net/10.1007/s11067-006-9012-5
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    Bibliographic Info

    Article provided by Springer in its journal Networks and Spatial Economics.

    Volume (Year): 7 (2007)
    Issue (Month): 3 (September)
    Pages: 241-256

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    Handle: RePEc:kap:netspa:v:7:y:2007:i:3:p:241-256

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    Web page: http://www.springerlink.com/link.asp?id=106607

    Related research

    Keywords: Vulnerability analysis; Combined travel demand model; Accessibility; Random utility;

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    Cited by:
    1. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    2. Seungkyu Ryu & Anthony Chen & Xiangdong Xu & Keechoo Choi, 2014. "A Dual Approach for Solving the Combined Distribution and Assignment Problem with Link Capacity Constraints," Networks and Spatial Economics, Springer, vol. 14(2), pages 245-270, June.
    3. Yao, Jia & Chen, Anthony & Ryu, Seungkyu & Shi, Feng, 2014. "A general unconstrained optimization formulation for the combined distribution and assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 137-160.
    4. Tuzun Aksu, Dilek & Ozdamar, Linet, 2014. "A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 56-67.
    5. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    6. Carrillo Murillo, David Guillermo & Liedtke, Gernot, 2013. "A model for the formation of colloidal structures in freight transportation: The case of hinterland terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 55-70.
    7. Bi Chen & William Lam & Agachai Sumalee & Qingquan Li & Hu Shao & Zhixiang Fang, 2013. "Finding Reliable Shortest Paths in Road Networks Under Uncertainty," Networks and Spatial Economics, Springer, vol. 13(2), pages 123-148, June.
    8. Lili Du & Srinivas Peeta, 2014. "A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions," Networks and Spatial Economics, Springer, vol. 14(2), pages 271-295, June.
    9. F. Parvaresh & S. Hashemi Golpayegany & S. Moattar Husseini & B. Karimi, 2013. "Solving the p-hub Median Problem Under Intentional Disruptions Using Simulated Annealing," Networks and Spatial Economics, Springer, vol. 13(4), pages 445-470, December.
    10. Chen, Bi Yu & Lam, William H.K. & Sumalee, Agachai & Li, Qingquan & Li, Zhi-Chun, 2012. "Vulnerability analysis for large-scale and congested road networks with demand uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 501-516.
    11. Yang, Chao & Chen, Anthony & Xu, Xiangdong & Wong, S.C., 2013. "Sensitivity-based uncertainty analysis of a combined travel demand model," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 225-244.

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