Network-based resilience assessment of an urban rail transit infrastructure with a multi-dimensional performance metric

Abstract

With urban and public transportation development, the urban rail transit networks (URTN) become increasingly complex, evolving into multi-layer and intricate systems. The operating environment is complex, and the rising frequency of emergencies significantly impacts the entire network. Consequently, the resilient ability of URTN to deal with risk attacks has become an important research field. In this paper, a bilayer URTN model is constructed, encompassing urban and suburban rail transit, proposing the adjacency matrix and the coupling mechanism of subnetworks. Then, the performance of a URTN jointly considering network efficiency, network structure entropy, and the number of trips per unit time is addressed. By considering passenger travel alternatives under disruptions, we develop an improved Logit stochastic user equilibrium (SUE) passenger assignment model based on generalized travel time costs, introducing the failure degree of the stations, to predict passenger flow paths. A multi-dimensional resilience assessment model is proposed using the resilience change curve for attack scenarios and recovery strategies, and a comprehensive network performance system through the AHP method to determine the weight coefficients of indicators. Finally, we present a case study based on the Shanghai URT network to explore the resilience of URTN in the morning peak and simulate the network resilience under different failure scenarios. The results indicate that the proposed model can assess the resilience of the Shanghai MRTN under random and malicious failure, and the former has less comprehensive performance losses and greater resilience. Additionally, the sensitivity analysis is conducted to explore the impact of the number of failed stations, the failure degree of stations, and recovery ability on network resilience. This study provides theoretical support for urban managers and builders regarding network structure and emergency management, and offers relevant suggestions.