Abstract
This paper presents a network analysis approach to simulate cascading effects in a transit network with the aim to assess its resilience and efficiency. The key element of a cascade is time: as time passes by, more locations or connections of the transit network which are nodes and edges of the associated graph can be affected consecutively as well as change their own condition. Thus, modifications in terms of efficiency and resilience are also dynamically evaluated and analysed along the cascade. Results on the two case studies of the RESOLUTE project (i.e., Florence, in Italy, and the Attika region, in Greece) are presented. Since the two case studies are significantly different, important differences are reflected also on the impacts of the relative cascades, even if they were started in both the two cases from the node with the highest betweenness centrality.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ash, J., Newth, D.: Optimizing complex networks for resilience against cascading failure. Phys. Stat. Mech. Appl. (2007). https://doi.org/10.1016/j.physa.2006.12.058
Buldyrev, S., Parshani, R., Paul, G., Stanley, H., Havlin, S.: Catastrophic cascade of failures in interdependent networks. Nature (2010). https://doi.org/10.1038/nature08932
Motter, A.: Cascade control and defense in complex networks. Phys. Rev. Lett. 93 (2004). https://doi.org/10.1103/PhysRevLett.93.098701
Phadke, A., Thorp, J.: Expose hidden failures to prevent cascading outages [in power systems]. Comput. Appl. Power IEEE (1996). https://doi.org/10.1109/67.526849
D’Lima, M., Medda, F.: A new measure of resilience: an application to the London Underground. Transp. Res. Part A Policy Practise (2015). https://doi.org/10.1016/j.tra.2015.05.017
Gutfraind, A.: Optimizing network topology for cascade resiliance. In: Handbook of Optimization in Complex Networks (2012). https://doi.org/10.1007/978-1-4614-0857-4_2
Candelieri, A., Archetti, F.: Detecting events and sentiment on twitter for improving urban mobility. ESSEM AAMAS 1351, 106–115 (2015)
Soldi, D., Candelieri, A., Archetti, F.: Resilience and vulnerability in urban water distribution networks through network theory and hydraulic simulation. Proc. Eng. 2015(119), 1259–1268 (2015). https://doi.org/10.1016/j.proeng.2015.08.990
Crucitti, P., Latora, V., Marchiori, M.: Model for cascading failures in complex networks. Phys. Rev. E. 69(4), 045–104 (2004). https://doi.org/10.1103/PhysRevE.69.045104
Lai, Y., Motter, A., Nishikawa, T.: Attacks and cascades in complex networks. Complex Netw. Lect. Notes Phys. (2004). https://doi.org/10.1007/978-3-540-44485-5_14
Nagurney, A., Qiang, Q.: A network efficiency measure for congested networks. EPL (Europhysics Letters) (2007). https://doi.org/10.1209/0295-5075/79/38005
Zou, Z., Xiao, Y., Gao, J.: Robustness analysis of urban transit network based on complex networks theory. Kybernetes 42(3), 383–399 (2013). https://doi.org/10.1108/03684921311323644
Von Ferber, C., Holovatch, T., Holovatch, Y., Palchykov, Y.: Public transport networks: empirical analysis and modeling. Eur. Phys. J. B (2009). https://doi.org/10.1140/epjb/e2009-00090-x
Freeman, L.C.: A set of measures of centrality based on betweenness. Sociometry (1977). https://doi.org/10.2307/3033543
Latora, V., Marchiori, M.: Efficient behavior of small-world networks. Phys. Rev. Lett. (2001). https://doi.org/10.1103/PhysRevLett.87.198701
Latora, V., Marchiori, M.: Is the Boston subway a small-world network? Phys. A Stat. Mech. Appl. (2002). https://doi.org/10.1016/S0378-4371(02)01089-0
Acknowledgements
This work has been supported by the RESOLUTE project (http://www.RESOLUTE-eu.org) and has been funded within the European Commissions H2020 Programme under contract number 653460. This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Candelieri, A., Giordani, I., Galuzzi, B.G., Archetti, F. (2018). Evaluation of Cascade Effects for Transit Networks. In: Daniele, P., Scrimali, L. (eds) New Trends in Emerging Complex Real Life Problems. AIRO Springer Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-00473-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-00473-6_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00472-9
Online ISBN: 978-3-030-00473-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)