Exploring cascading reliability of multi-modal public transit network based on complex networks

Lin Zhang, Huiying Wen, Jian Lu, Da Lei, Shubin Li and Satish V. Ukkusuri

Reliability Engineering and System Safety, 2022, vol. 221, issue C

Abstract: Previous studies had focused on cascading failures of urban rail transit network (URTN) or bus transit network (BTN) while ignoring their coupling performances against cascading failures. Particularly, when considering the embedded effect of the other transit modes network (OTN, i.e., private cars and taxis sharing road infrastructures with BTN), cascading failures of multi-modal public transit network (MPTN) exhibit complex coupling dynamics caused by the intertwining and coupling effect of three types of failure load dynamic redistributions (FLDRs in a single layer or between layers). This work proposes a cascading reliability model to model, measure, and control this special type of cascading failures, which provides a novel perspective to test the entire network reliability with a unique advantage of calculation efficiency based on complex networks. Then, a case study concerning the cascading failures of an MPTN under impacts of a large passenger flow from a large-scale integrated passenger hub station is conducted. Results show that the proposed model has good adaptability, and its 5 / 6 control parameters have a different but effective correlation with cascading reliability and can realize the controllability of cascading reliability. Furthermore, the proposed multiple evaluation indicators of cascading reliability realize the diversity of measuring perspectives and demonstrate good mutual verification performances.

Keywords: Cascading failures; Reliability; Complex networks; Load-capacity model; Failure load dynamic redistributions (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:221:y:2022:i:c:s095183202200045x

DOI: 10.1016/j.ress.2022.108367

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