This paper presents a network analysis approach to assess efficiency and resilience of public transport systems under cascading failures. Results of the two case studies of the RESOLUTE project (i.e., Florence, Italy and the Attika region, Greece) are presented. Failures can be of different types (accidents, infrastructure collapses, attacks, etc.) and can lead to impacts with different severities. The key element of cascading failures is time: as time passes by, more locations or connections of the network can be affected consecutively, as well as change their own condition. The proposed network analysis approach simulates failure propagation and evaluates the associated impacts on the transport system. Analogously to the analysis of road networks proposed in the literature, the network average efficiency and the relative size of the largest connected component have been considered for the analysis of the two RESOLUTE case studies. The cascade is simulated as follows. The node betweenness – the number of shortest paths through that node (i.e. stop/station) – is the “capacity” of that node. The worst-case of the cascading failure is considered. The node with the highest betweenness is the one triggering the cascade: it is removed and the new betweenness for every remaining node is computed, since it changes with the new shortest paths arrangement. All the nodes with betweenness higher than capacity are removed and the process continues until no more nodes can be deleted, that is the end of the cascade. Finally, efficiency and relative size of the largest connected component are computed along the cascade, to compare network at the begin and the end of the cascade. Analysis is repeated by considering the chance to increase node capacity by a given percentage, allowing to assess which is the implied improvement on resilience and on efficiency supporting a more sustainable allocation of financial resources.
Candelieri, A., Giordani, I., Galuzzi, B., Archetti, F. (2019). Efficiency and resilience assessment under cascading failures in transit networks. In F.A. Ortega Riejos, C.A. Brebbia (a cura di), Urban Transport XXIV (pp. 177-186). WITPress [10.2495/UT180171].
Efficiency and resilience assessment under cascading failures in transit networks
Candelieri, A;Giordani, I;Galuzzi, BG
;Archetti, F
2019
Abstract
This paper presents a network analysis approach to assess efficiency and resilience of public transport systems under cascading failures. Results of the two case studies of the RESOLUTE project (i.e., Florence, Italy and the Attika region, Greece) are presented. Failures can be of different types (accidents, infrastructure collapses, attacks, etc.) and can lead to impacts with different severities. The key element of cascading failures is time: as time passes by, more locations or connections of the network can be affected consecutively, as well as change their own condition. The proposed network analysis approach simulates failure propagation and evaluates the associated impacts on the transport system. Analogously to the analysis of road networks proposed in the literature, the network average efficiency and the relative size of the largest connected component have been considered for the analysis of the two RESOLUTE case studies. The cascade is simulated as follows. The node betweenness – the number of shortest paths through that node (i.e. stop/station) – is the “capacity” of that node. The worst-case of the cascading failure is considered. The node with the highest betweenness is the one triggering the cascade: it is removed and the new betweenness for every remaining node is computed, since it changes with the new shortest paths arrangement. All the nodes with betweenness higher than capacity are removed and the process continues until no more nodes can be deleted, that is the end of the cascade. Finally, efficiency and relative size of the largest connected component are computed along the cascade, to compare network at the begin and the end of the cascade. Analysis is repeated by considering the chance to increase node capacity by a given percentage, allowing to assess which is the implied improvement on resilience and on efficiency supporting a more sustainable allocation of financial resources.File | Dimensione | Formato | |
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