Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 586, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.physa.2021.126465
Keywords
Resilience; Urban road network; Cascading failure; Load-capacity model; Deliberate attack; Random attack
Categories
Funding
- 111 project of Sustainable Transportation for Urban Agglomeration in Western China [B20035]
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This study proposed a resilience assessment framework for urban road networks, showing that intersection-based attacks have a significant impact on resilience, and resilience is positively correlated with the node degree of the attacked intersection. Increasing alpha and beta can enhance resilience, and the urban road network achieves the best resilience performance when alpha = 0.3, beta = 0.5.
Urban space for new transportation facilities cannot meet the increasing traffic demand. Afterward, scholars gradually increased attention to the resilience evaluation of urban road networks. Therefore, we proposed a resilience assessment framework of the urban road networks, including the resilience performance index, the robustness index, and the recovery index. Then we simulated the cascading failure based on a nonlinear load-capacity model with two capacity control parameters: alpha and beta. Results show that the intersection-based attack has the most significant impact on resilience, and resilience is positively correlated with the node degree of the attacked intersection. The increase of alpha and beta could enhance the resilience, and the urban road network achieves the best resilience performance when alpha = 0.3, beta = 0.5. Compared with the deliberate attack strategy, the resilience performance under the random attack strategy is more robust. This research can provide the foundation for optimizing urban road networks and multi-mode urban public transit networks. (C) 2021 Elsevier B.V. All rights reserved.
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