Robustness Analysis of High-Speed Railway Networks Against Cascading Failures: From a Multi-Layer Network Perspective

IF 6.7 2区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY IEEE Transactions on Network Science and Engineering Pub Date : 2024-08-28 DOI:10.1109/TNSE.2024.3451118
Junfeng Ma;Shan Ma;Xiaotian Xie;Weihua Gui
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Abstract

In this study, we model the high-speed railway (HSR) network as a directed multi-layer network. Specifically, each node is viewed as a tuple of a train with a station it passes through. A directed edge within a layer means that a train passes through two consecutive stations in its scheduled train route, while an edge between different layers means that two trains pass through the same station sequentially. Then we assess the robustness against cascading failures of these multi-layer networks by introducing metrics such as network efficiency and the ratio of failed nodes under disturbances. Furthermore, we propose a cascading failure model based on train delay propagation to investigate the cascading dynamics within the multi-layer HSR network. To better characterize the delay propagation patterns in the network, train delays at each station are treated as the load of the corresponding node, while the time supplements and buffer time are considered as the capacities of the edges. Finally, we propose two strategies to enhance the robustness of HSR networks against cascading failures. Numerical experiments are conducted to demonstrate the effectiveness of these strategies.
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高速铁路网对级联故障的鲁棒性分析:从多层网络的角度
在本研究中,我们将高速铁路(HSR)网络建模为有向多层网络。具体来说,每个节点都被视为列车和列车经过的车站的元组。层内的有向边表示一列列车在其预定列车路线中连续经过两个车站,而不同层之间的边表示两列列车依次经过同一车站。然后,我们通过引入网络效率和干扰下故障节点比率等指标,评估这些多层网络对级联故障的鲁棒性。此外,我们还提出了基于列车延迟传播的级联故障模型,以研究多层高铁网络内的级联动态。为了更好地描述网络中的延迟传播模式,我们将各站的列车延迟视为相应节点的负载,而将时间补充和缓冲时间视为边缘的容量。最后,我们提出了两种策略来增强高铁网络对级联故障的鲁棒性。我们通过数值实验证明了这些策略的有效性。
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来源期刊
IEEE Transactions on Network Science and Engineering
IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering
CiteScore
12.60
自引率
9.10%
发文量
393
期刊介绍: The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.
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