Identification of critical stations in a Metro System: A substitute complex network analysis

Metro systems are critical public transport elements in several metropolitan areas around the world. Unexpected disruptions may undermine service provision of metro systems, and thus addressing their negative impacts is of primary importance. A first step towards developing mitigation measures invol...

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Veröffentlicht in:Physica A 2022-06, Vol.596, p.127123, Article 127123
Hauptverfasser: Kopsidas, Athanasios, Kepaptsoglou, Konstantinos
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Sprache:eng
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Zusammenfassung:Metro systems are critical public transport elements in several metropolitan areas around the world. Unexpected disruptions may undermine service provision of metro systems, and thus addressing their negative impacts is of primary importance. A first step towards developing mitigation measures involves the identification of those critical metro stations, whose operation must be preserved. Complex Network Theory (CNT) provides valuable methodological tools for this purpose, as a topological analysis based on centrality measures combined with real-world spatiotemporal data can be used for critical station identification. The objective of this paper is to develop a measure for evaluating metro station criticality based on CNT, considering substitute services during a disruption. A substitute network is defined as the network consisting of the metro stations as nodes and all alternative public transport routes potentially serving those stations outside the metro system, as edges. The form of the substitute network depends on a pre-selected service level. Two graphs are constructed, the metro and the substitute, using an L-space and a P-space representation, respectively. A combination of centrality measures of both networks is utilized for evaluating the stations’ criticality. The methodology proposed is applied to a real-world metro system, that of Athens, Greece. A sensitivity analysis is conducted suggesting that the proposed measures manage to capture the tradeoff between centrality and availability of alternatives, considering a station’s topological criticality. On top of that, the criticality measure seems to be robust against changes at service levels, but sensitive enough, so that it can be adaptable to each operator’s needs. The methodology proposed can be utilized for identifying critical metro stations a priori and thus achieving a more efficient planning, considering metro disruptions.
ISSN:0378-4371
1873-2119
DOI:10.1016/j.physa.2022.127123