Analysis of Cascading Failures and Recovery in Freeway Network Under the Impact of Incidents
In the past few decades, extensive research has been conducted on the modeling of cascading failures and their recovery processes in freeway networks. In practice, the restoration of functionality and structure in complex networks that suffer large-scale cascading failures may involve a series of re...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/13/7276 |
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| Summary: | In the past few decades, extensive research has been conducted on the modeling of cascading failures and their recovery processes in freeway networks. In practice, the restoration of functionality and structure in complex networks that suffer large-scale cascading failures may involve a series of repair operations. In this paper, we first propose a cascading failure model for freeway networks, which considers load redistribution by taking travelers’ choice behavior into account. Specifically, we use the Stochastic User Equilibrium (SUE) as a method for redistribution in the model. Next, we propose a recovery strategy focused on critical edges, with their importance ranked through the integration of the network’s topological features and traffic characteristics. This ranking then serves as the foundation for the edge-recovery process. This model considers the operational mechanisms of complex freeway networks. In the experiment, we used the freeway network in Hunan Province as a case study to validate the effectiveness of our model. Traffic volume data were collected from toll stations on the freeway network, and the topological structure of the network was combined with these data to construct a complex weighted freeway network. The evolution of network cascading failures was analyzed under various scenarios of attacks caused by traffic incidents. Subsequently, the failed network was recovered, and the results indicate that the proposed recovery strategy demonstrates better performance compared to other traditional methods. This research provides theoretical and methodological support for the management of freeway networks. |
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| ISSN: | 2076-3417 |