Resilience of Urban Rail Network Under Large Passenger Flow

In response to growing urban economies and increased emphasis on communal public transit, the recurrent phenomenon of large passenger flows has become a focal point of study. This research introduces a self-healing cascading failure passenger flow propagation model and employs resilience as the metric for network performance. Initially, the influence of model parameters is explored through simulation. Subsequently, the performance of the network after disruptions at various stations is examined, using Xi'an rail transit as a case study. Ultimately, the study investigates the effects of various passenger evacuation ratios, revealing that when these ratios range between 0.4 and 0.5, the impact on network resilience is negligible. The findings suggest that the proposed model possesses significant applicative potential for assessing network dynamic performance under large passenger flow conditions. Moreover, it offers a theoretical underpinning for the effective management and operation of metro systems.

I. Introduction

Urban public transport (UPT), a crucial element of urban infrastructure, plays a significant role in the broader context of urban transportation systems. Therefore, the need for meticulous analysis of urban transport resilience is growing [1]. Attacks on urban infrastructure can incur substantial losses, and numerous studies have explored the vulnerability of such infrastructure to natural disasters [2]. Additionally, various scholars have examined disruptions in urban subway systems due to operational incidents or accidents. Yin et al. [3] conducted a quantitative analysis of the resilience of urban rail transit systems against disruptions. Zhang et al. [4] assessed the vulnerability of Shanghai's Metro network in the face of node and line failures. Sun et al. [5] examined the vulnerability of the Shanghai Metro network from an operational standpoint, considering the relative probabilities of line disruptions.