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2018 | OriginalPaper | Buchkapitel

Assessing Urban Rail Transit Systems Vulnerability: Metrics vs. Interdiction Models

verfasst von : Stefano Starita, Annunziata Esposito Amideo, Maria Paola Scaparra

Erschienen in: Critical Information Infrastructures Security

Verlag: Springer International Publishing

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Abstract

Urban rail transit systems are highly vulnerable to disruptions, including accidental failures, natural disasters and terrorist attacks. Due to the crucial role that railway infrastructures play in economic development, productivity and social well-being of communities, evaluating their vulnerability and identifying their most critical components is of paramount importance. Two main approaches can be deployed to assess transport infrastructure vulnerabilities: vulnerability metrics and interdiction models. In this paper, we compare these two approaches and apply them to the Central London Tube to identify the most critical stations with respect to accessibility, efficiency and flow measures.

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Addis, B., Di Summa, M., Grosso, A.: Identifying critical nodes in undirected graphs: complexity results and polynomial algorithms for the case of bounded treewidth. Discret. Appl. Math. 161(16), 2349–2360 (2013)MathSciNetCrossRef

Arulselvan, A., Commander, C.W., Elefteriadou, L., Pardalos, P.M.: Detecting critical nodes in sparse graphs. Comput. Oper. Res. 36(7), 2193–2200 (2009)MathSciNetCrossRef

Balijepalli, C., Oppong, O.: Measuring vulnerability of road network considering the extent of serviceability of critical road links in urban areas. J. Transp. Geogr. 39, 145–155 (2014)CrossRef

7/7 London bombings: What happened on 7 July 2005? (2015). CBBC Newsround. Accessed 23 June 2017

Cappanera, P., Scaparra, M.P.: Optimal allocation of protective resources in shortest-path networks. Transp. Sci. 45(1), 64–80 (2011)CrossRef

Church, R.L., Scaparra, M.P., Middleton, R.S.: Identifying critical infrastructure: the median and covering facility interdiction problems. Ann. Assoc. Am. Geogr. 94(3), 491–502 (2004)CrossRef

Esposito Amideo, A., Scaparra, M.P.: A synthesis of optimization approaches for tackling critical information infrastructure survivability. In: Havarneanu, G., Setola, R., Nassopoulos, H., Wolthusen, S. (eds.) CRITIS 2016. LNCS, vol. 10242, pp. 75–87. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-71368-7_7CrossRef

Fulkerson, D.R., Harding, G.C.: Maximizing the minimum source-sink path subject to a budget constraint. Math. Program. 13(1), 116–118 (1977)MathSciNetCrossRef

Granata, D., Steeger, G., Rebennack, S.: Network interdiction via a critical disruption path: branch-and-price algorithms. Comput. Oper. Res. 40(11), 2689–2702 (2013)MathSciNetCrossRef

10.

Gillett, F.: London Bridge station: commuters warned of major disruption on trains for rest of evening. Evening Standard (2017). Accessed 23 June 2017

11.

Harley, N.: Fire at Euston Station continues to cause rail disruption. The Telegraph (2017). Accessed 23 June 2017

12.

Jenelius, E., Petersen, T., Mattsson, L.G.: Importance and exposure in road network vulnerability analysis. Transp. Res. Part A: Policy Pract. 40(7), 537–560 (2006)

13.

Kim, I.Y., de Weck, O.L.: Adaptive weighted-sum method for bi-objective optimization: pareto front generation. Struct. Multidiscip. Optim. 29(2), 149–158 (2005)CrossRef

14.

Mach, K., Mastrandrea, M.: In: Field, C.B., Barros, V.R. (eds.) Climate Change 2014: Impacts, Adaptation, and Vulnerability. Cambridge University Press, Cambridge and New York (2014)

15.

Matisziw, T.C., Murray, A.T.: Modeling st path availability to support disaster vulnerability assessment of network infrastructure. Comput. Oper. Res. 36(1), 16–26 (2009)CrossRef

16.

Murray, A.T.: An overview of network vulnerability modeling approaches. GeoJournal 78(2), 209–221 (2013)CrossRef

17.

Office of Rail and Road: Statistical releases (2017). Accessed 23 June 2017

18.

Ouyang, M., Zhao, L., Hong, L., Pan, Z.: Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability. Reliab. Eng. Syst. Saf. 123, 38–46 (2014)CrossRef

19.

Scott, D.M., Novak, D.C., Aultman-Hall, L., Guo, F.: Network robustness index: a new method for identifying critical links and evaluating the performance of transportation networks. J. Transp. Geogr. 14(3), 215–227 (2006)CrossRef

20.

Starita, S., Scaparra, M.P.: Passenger railway network protection: a model with variable post-disruption demand service. J. Oper. Res. Soc. 69(4), 1–18 (2017)

21.

Sullivan, J., Aultman-Hall, L., Novak, D.: A review of current practice in network disruption analysis and an assessment of the ability to account for isolating links in transportation networks. Transp. Lett. 1(4), 271–280 (2009)CrossRef

22.

Sun, D.J., Zhao, Y., Lu, Q.C.: Vulnerability analysis of urban rail transit networks: a case study of Shanghai, China. Sustainability 7(6), 6919–6936 (2015)CrossRef

23.

Veremyev, A., Prokopyev, O.A., Pasiliao, E.L.: An integer programming framework for critical elements detection in graphs. J. Comb. Optim. 28(1), 233–273 (2014)MathSciNetCrossRef

24.

Wang, J.W., Rong, L.L.: Cascade-based attack vulnerability on the US power grid. Saf. Sci. 47(10), 1332–1336 (2009)CrossRef

25.

Wollmer, R.: Removing arcs from a network. Oper. Res. 12(6), 934–940 (1964)MathSciNetCrossRef

Titel: Assessing Urban Rail Transit Systems Vulnerability: Metrics vs. Interdiction Models
verfasst von: Stefano Starita
Annunziata Esposito Amideo
Maria Paola Scaparra
Verlag: Springer International Publishing
Buch: Critical Information Infrastructures Security
Print ISBN: 978-3-319-99842-8

Electronic ISBN: 978-3-319-99843-5

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-99843-5_13

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