Vulnerability of public transportation networks against directed attacks and cascading failures

This paper presents some results devoted to providing network analysis functionalities for vulnerability assessment in public transportation networks with respect to disruptive events and/or targeted attacks to stations. The results have been obtained on two public transportation networks: the bus network in Florence, Italy, and the transportation network in the Attika region, Greece. The analysis implements a topological approach, based on graph theory, using a multi-graph to model public transportation networks and analyse vulnerabilities with respect to the removal of one or more of their components. Both directed attacks and cascading failures are considered. While the first type of disruptive events is related to a static analysis, where nodes are removed according to a rank related to some centrality measures, the second type is related to a dynamic analysis, where a failure cascade is simulated making unavailable the node with the highest betweenness value. Vulnerability measures are computed as loss of connectivity and efficiency, with respect to both the two different types of disruptive events considered. This study allows to evidence potential vulnerabilities of the urban networks, that must be considered to support the planning process into the creation of resilient structures.

[1]  Francesco Archetti,et al.  NETWORK ANALYSIS FOR RESILIENCE EVALUATION IN WATER DISTRIBUTION NETWORKS , 2015 .

[2]  Juan Carlos García-Palomares,et al.  Measuring the vulnerability of public transport networks , 2014 .

[3]  P. Bonacich Factoring and weighting approaches to status scores and clique identification , 1972 .

[4]  C. von Ferber,et al.  Attack Vulnerability of Public Transport Networks , 2007, 0709.3206.

[5]  Erik Jenelius,et al.  Road network vulnerability analysis: Conceptualization, implementation and application , 2015, Comput. Environ. Urban Syst..

[6]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[7]  Katja Berdica,et al.  AN INTRODUCTION TO ROAD VULNERABILITY: WHAT HAS BEEN DONE, IS DONE AND SHOULD BE DONE , 2002 .

[8]  V. Latora,et al.  Multiscale vulnerability of complex networks. , 2007, Chaos.

[9]  Massimo Marchiori,et al.  Vulnerability and protection of infrastructure networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Yurij Holovatch,et al.  Public Transport Networks under Random Failure and Directed Attack , 2010 .

[11]  Erik Jenelius,et al.  Planning for the unexpected: The value of reserve capacity for public transport network robustness , 2015 .

[12]  Beom Jun Kim,et al.  Attack vulnerability of complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[14]  Yogesh Virkar,et al.  Power-law distributions in binned empirical data , 2012, 1208.3524.

[15]  G. Zocchi,et al.  Local cooperativity mechanism in the DNA melting transition. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  D. Newth,et al.  Optimizing complex networks for resilience against cascading failure , 2007 .

[17]  Ernesto Estrada,et al.  Network robustness to targeted attacks. The interplay of expansibility and degree distribution , 2006 .

[18]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[19]  Miguel Romance,et al.  Structural Vulnerability and Robustness in Complex Networks: Different Approaches and Relationships Between them , 2012 .

[20]  Erik Jenelius,et al.  The value of new public transport links for network robustness and redundancy , 2015 .

[21]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[22]  J. C. G. Palomares,et al.  Measuring the vulnerability of public transport networks , 2014 .

[23]  Paolo Nesi,et al.  Towards resilience operationalization in urban transport system: The RESOLUTE project approach , 2017 .

[24]  Francesco Archetti,et al.  Resilience and Vulnerability in Urban Water Distribution Networks through Network Theory and Hydraulic Simulation , 2015 .

[25]  V. Palchykov,et al.  Public transport networks: empirical analysis and modeling , 2008, 0803.3514.

[26]  Erik Jenelius,et al.  Vulnerability and resilience of transport systems : A discussion of recent research , 2015 .

[27]  Oded Cats,et al.  Exposing the role of exposure: Public transport network risk analysis , 2016 .

[28]  V. Latora,et al.  A measure of centrality based on network efficiency , 2004, cond-mat/0402050.

[29]  Yao Xiao,et al.  Robustness analysis of urban transit network based on complex networks theory , 2013, Kybernetes.

[30]  Erik Jenelius,et al.  Beyond a complete failure: the impact of partial capacity degradation on public transport network vulnerability , 2018 .

[31]  Elise Miller-Hooks,et al.  Assessing the role of network topology in transportation network resilience , 2015 .

[32]  David I Blockley,et al.  Vulnerability of structural systems , 2003 .

[33]  Alexander Gutfraind,et al.  Optimizing Network Topology for Cascade Resilience , 2012 .

[34]  Cohen,et al.  Resilience of the internet to random breakdowns , 2000, Physical review letters.