Strategies to Enhance the Resilience of an Urban Rail Transit Network
An urban rail transit (URT) system is an important component of an urban infrastructure system; however, it is vulnerable to disturbances, such as natural disasters and terrorist attacks. Constructing a highly resilient URT network has practical significance for enhancing its capability to respond t...
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Veröffentlicht in: | Transportation research record 2022-01, Vol.2676 (1), p.342-354 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | An urban rail transit (URT) system is an important component of an urban infrastructure system; however, it is vulnerable to disturbances, such as natural disasters and terrorist attacks. Constructing a highly resilient URT network has practical significance for enhancing its capability to respond to disturbances. In this paper, models are developed to optimize a URT network’s structure with regard to resilience and to enhance the resilience of a disrupted URT network. A bi-level programming model that aims to maximize a URT network’s global accessibility and global efficiency is formulated to optimize the structure of the network. A novel repair strategy, called the simulation repair strategy, is proposed to enhance the resilience of a disrupted URT network by optimizing the repair sequence of failed stations. The models are utilized to enhance the resilience of the Chengdu subway network. The result indicates that the bi-level programming model guides the construction of new links to optimize the structure of the Chengdu subway network. Deliberate attacks are more harmful to the Chengdu subway network than random attacks. The network’s operators need to pay attention to the operations of critical stations (e.g., Chunxi Road station and Tianfu Square station) to prevent disturbances from exerting considerable negative effects on the network’s normal operations. The simulation repair strategy exhibits higher repair efficiency than the conventional repair strategy, and it effectively enhances the resilience of the disrupted Chengdu subway network. |
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ISSN: | 0361-1981 2169-4052 |
DOI: | 10.1177/03611981211037888 |