4.6 Article

Metropolitan rail network robustness

出版社

ELSEVIER
DOI: 10.1016/j.physa.2020.124317

关键词

Transport network; Robustness; Network structure; Critical infrastructure; Disruptions; Line closure

资金

  1. European Union's Horizon 2020 SETA project [688082]

向作者/读者索取更多资源

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. (C) 2020 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据