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Assessing Protection Strategies for Urban Rail Transit Systems: A Case-Study on the Central London Underground

Author

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  • Annunziata Esposito Amideo

    (UCD Quinn School of Business, University College Dublin, Dublin, Ireland)

  • Stefano Starita

    (Sasin School of Management, Chulalongkorn University, Bangkok 10330, Thailand)

  • Maria Paola Scaparra

    (Centre for Logistics and Heuristic Optimisation (CLHO), Kent Business School, University of Kent, Canterbury CT2 7FS, UK)

Abstract

Urban rail transit systems are highly prone to disruptions of various nature (e.g., accidental, environmental, man-made). Railway networks are deemed as critical infrastructures given that a service interruption can prompt adverse consequences on entire communities and lead to potential far-reaching effects. Hence, the identification of optimal strategies to mitigate the negative impact of disruptive events is paramount to increase railway systems’ resilience. In this paper, we investigate several protection strategies deriving from the application of either single asset vulnerability metrics or systemic optimization models. The contribution of this paper is threefold. Firstly, a single asset metric combining connectivity, path length and flow is defined, namely the Weighted Node Importance Evaluation Index (WI). Secondly, a novel bi-level multi-criteria optimisation model, called the Railway Fortification Problem (RFP), is introduced. RFP identifies protection strategies based on stations connectivity, path length, or travel demand, considered as either individual or combined objectives. Finally, two different protection strategy approaches are applied to a Central London Underground case study: a sequential approach based on single-asset metrics and an integrated approach based on RFP. Results indicate that the integrated approach outperforms the sequential approach and identifies more robust protection plans with respect to different vulnerability criteria.

Suggested Citation

  • Annunziata Esposito Amideo & Stefano Starita & Maria Paola Scaparra, 2019. "Assessing Protection Strategies for Urban Rail Transit Systems: A Case-Study on the Central London Underground," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:22:p:6322-:d:285766
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    1. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    2. Stefano Starita & Maria Paola Scaparra, 2018. "Passenger railway network protection: a model with variable post-disruption demand service," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(4), pages 603-618, April.
    3. Wang, Xiangrong & Koç, Yakup & Derrible, Sybil & Ahmad, Sk Nasir & Pino, Willem J.A. & Kooij, Robert E., 2017. "Multi-criteria robustness analysis of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 19-31.
    4. Xu, Peijuan & Corman, Francesco & Peng, Qiyuan & Luan, Xiaojie, 2017. "A train rescheduling model integrating speed management during disruptions of high-speed traffic under a quasi-moving block system," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 638-666.
    5. Yingying Xing & Jian Lu & Shengdi Chen & Sunanda Dissanayake, 2017. "Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai Metro," Public Transport, Springer, vol. 9(3), pages 501-525, October.
    6. Starita, Stefano & Scaparra, Maria Paola, 2016. "Optimizing dynamic investment decisions for railway systems protection," European Journal of Operational Research, Elsevier, vol. 248(2), pages 543-557.
    7. Tony H. Grubesic & Timothy C. Matisziw & Alan T. Murray & Diane Snediker, 2008. "Comparative Approaches for Assessing Network Vulnerability," International Regional Science Review, , vol. 31(1), pages 88-112, January.
    8. Gerald Brown & Matthew Carlyle & Javier Salmerón & Kevin Wood, 2006. "Defending Critical Infrastructure," Interfaces, INFORMS, vol. 36(6), pages 530-544, December.
    9. Sarhadi, Hassan & Tulett, David M. & Verma, Manish, 2017. "An analytical approach to the protection planning of a rail intermodal terminal network," European Journal of Operational Research, Elsevier, vol. 257(2), pages 511-525.
    10. Jin, Jian Gang & Lu, Linjun & Sun, Lijun & Yin, Jingbo, 2015. "Optimal allocation of protective resources in urban rail transit networks against intentional attacks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 73-87.
    11. Kelly J. Cormican & David P. Morton & R. Kevin Wood, 1998. "Stochastic Network Interdiction," Operations Research, INFORMS, vol. 46(2), pages 184-197, April.
    12. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    13. Francis, Royce & Bekera, Behailu, 2014. "A metric and frameworks for resilience analysis of engineered and infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 90-103.
    14. Paola Cappanera & Maria Paola Scaparra, 2011. "Optimal Allocation of Protective Resources in Shortest-Path Networks," Transportation Science, INFORMS, vol. 45(1), pages 64-80, February.
    15. Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    16. Myung, Young-Soo & Kim, Hyun-joon, 2004. "A cutting plane algorithm for computing k-edge survivability of a network," European Journal of Operational Research, Elsevier, vol. 156(3), pages 579-589, August.
    17. Richard Wollmer, 1964. "Removing Arcs from a Network," Operations Research, INFORMS, vol. 12(6), pages 934-940, December.
    18. O'Hanley, Jesse R. & Church, Richard L., 2011. "Designing robust coverage networks to hedge against worst-case facility losses," European Journal of Operational Research, Elsevier, vol. 209(1), pages 23-36, February.
    19. Hyun Kim & Yena Song, 2018. "An integrated measure of accessibility and reliability of mass transit systems," Transportation, Springer, vol. 45(4), pages 1075-1100, July.
    20. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    21. Losada, Chaya & Scaparra, M. Paola & O’Hanley, Jesse R., 2012. "Optimizing system resilience: A facility protection model with recovery time," European Journal of Operational Research, Elsevier, vol. 217(3), pages 519-530.
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    3. Xiaojuan Li & Lulu Li & Mingchao Lin & Chi Yung Jim, 2022. "Research on Risk and Resilience Evaluation of Urban Underground Public Space," IJERPH, MDPI, vol. 19(23), pages 1-21, November.

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