Bridging strategy for the disruption of metro considering the reliability of transportation system: Metro and conventional bus network. (September 2022)

• Record Type: Journal Article
• Authors: Zheng, Shuai; Liu, Yugang; Lin, Yexin; Wang, Qiang; Yang, Hongtai; Chen, Bin
• Is Part Of: Reliability engineering & system safety. Volume 225(2022)
• Publication Date: 2022-09
• Subjects: System reliability -- Metro disruption -- Emergency strategy -- Bus bridging -- Bi-level programming -- Genetic algorithm; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2022.108585
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: An integrated, flexible, economical and considerate bridging strategy is proposed. The strategy can effectively cope with the sudden drop in metro reliability. To be more realistic, the strategy considers hindered passengers' heterogeneity. A bi-level programming model is established to describe the strategy. The strategy has remarkable superiority in comparing delay and response time. Abstract: With the frequent occurrence of metro disruption, how to guarantee the reliability of the system has gradually become a research hotspot. Previous studies mostly used the bridging bus to maintain the service level, and ignored the experience of passengers, the reliability of conventional bus system, the heterogeneity of passenger and underutilized the capacity. Hence, to deal with the deficiencies, a comprehensive bridging strategy is proposed to balance the benefit of stranded metro passengers and conventional bus passengers considering the dynamic changes in passenger demand. We develop a tailor-made integration framework for operators, dispatch bridging buses from multiple alternative sources, and design two operated access methods: Station-Station docking method and demand-responsive method to satisfy the heterogeneity of passenger. A bi-level programming model is established to describe the strategy and to determine operation scheme. And then, a two-layer multi-objective genetic algorithm is used to solve the bi-level model. A case study is conducted based on the real case of Guangzhou Metro disruption in 2019. The superiority of the proposed strategy over the two benchmark strategies is demonstrated by the results. Notably, the study provides some suitable and operable evacuation strategy for transit operators to guarantee residents' daily travel plan with the sensitivity analysis.