{"title":"Robustness Analysis of High-Speed Railway Networks Against Cascading Failures: From a Multi-Layer Network Perspective","authors":"Junfeng Ma;Shan Ma;Xiaotian Xie;Weihua Gui","doi":"10.1109/TNSE.2024.3451118","DOIUrl":null,"url":null,"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.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"11 6","pages":"6522-6534"},"PeriodicalIF":6.7000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10654552/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
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.
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.