Assessment of Urban Rail Transit System Resilience Based on a Cloud Matter-Element Model

AbstractTo ensure the operational reliability and service quality of urban rail transit systems, it is crucial to assess the resilience of urban rail transit reasonably when subjected to disruptions. This paper divides the resilience of an urban rail transit system into absorption, buffering, and recovery phases according to the characteristics of resilience changes, based on which a resilience evaluation index was developed. Then the order relation analysis-criteria important through intercriteria correlation (G1-CRITIC) method was employed for subjective-objective combination weighting to determine the comprehensive weights of the evaluation indexes. After that, a cloud model was combined with a matter-element theory to construct a cloud matter-element assessment model, which aimed at addressing the fuzziness and randomness that may occur during the assessment process. The proposed model was applied to the Dalian, China, urban rail transit system as a case study. The resilience assessment was conducted based on four quantitative indicators acquired from field surveys and scores of 16 qualitative indicators obtained through expert interviews. Results showed that the maximum comprehensive membership degree of resilience for Dalian urban rail transit system is 0.3074, which was rated as having moderate resilience. Among the secondary indicators in the absorption phase, transit line substitutability fell under the extremely weak resilience grade, with a substitutability rate accounting for 26.9% of the total operational length of transit lines. The research findings have the potential to provide urban rail transit operators and planners with a clearer view of the vulnerable routes or stations, facilitating the adoption of proactive measures to enhance the system’s ability to withstand disruptions. Moreover, the case study demonstrated that the cloud matter-element combination model is highly applicable for assessing the resilience of urban rail transit systems.