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Metropolitan rail network robustness

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  • Cats, Oded
  • Krishnakumari, Panchamy

Abstract

In large-scale urban agglomerations, heavy rail in the form of metro and commuter train serves as the backbone of the metropolitan public transport network. The objective of this paper is to investigate whether networks with strikingly different structure and development pattern exhibit different robustness properties in the event of random and targeted attacks. We adopt a complex network theory approach, investigating network performances under alternative sequential disruption scenarios corresponding to the successive closure of either stations or track segments. We also investigate the case where the removal of a network node or link implies the closure of all traversing lines Network performance is measured both in terms of the capacity of the network to function in terms of connectivity as well as the additional impedance induced for those that remain connected. An aggregate robustness indicator based on the integral of the deterioration of network performance is adopted. Three exemplary networks are selected, the urban rail networks of London, Shanghai and Randstad. These three networks offer showcases of short and long development patterns, mono- and polycentric agglomeration structures, including the largest and the oldest metropolitan heavy rail networks. The polycentric network of the Randstad was found the least robust in this analysis when compared to the more monocentric networks of London and Shanghai. The London network is in general more robust than the Shanghai network thanks to the presence of cycles beyond the core. Our findings provide more nuanced evidence on the relation between network structure and development pattern, and its robustness.

Suggested Citation

  • Cats, Oded & Krishnakumari, Panchamy, 2020. "Metropolitan rail network robustness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
  • Handle: RePEc:eee:phsmap:v:549:y:2020:i:c:s0378437120301047
    DOI: 10.1016/j.physa.2020.124317
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