On the dynamic vulnerability of an urban rail transit system and the impact of human mobility

Abstract

Urban rail transit (URT) plays a pivotal role in facilitating human mobility within urban environments. It is significant to understand its vulnerability, i.e., the variation in capacity and demand when confronted with unexpected events, particularly operational disruptions. Although the network topology is generally fixed, the hourly-changing travel demand greatly impacts the actual vulnerability of a URT system. Unfortunately, few existing studies consider the combined influence of dynamic travel demand and network topology. To fill the gap, this paper proposes a network vulnerability assessment method with the joint consideration of static network topology and dynamic travel demand. This method includes a defined reasonable path, an accessibility-based identification of station importance with time-varying passenger demand, and a new dynamic vulnerability delay index considering affected travel demand. An empirical analysis was carried out by taking the URT system of Beijing, China as an example, and the impact of the more realistic multiple consecutive station failures in a URT system is also examined. Results show that the distribution of high-importance stations indeed varies with the time of day, affected by both static topology and hourly-changing passenger flow. When the disturbance of operation delay occurs, the impact of high-importance stations on the network vulnerability changes nonlinearly with the increase of delayed travel demand. Some stations that serve as bridges and are visited by large passenger flows have the greatest impact on network vulnerability. Network performance degradation is obviously segmented and stratified in the case of interval continuous failure. The disruption between different lines is the main cause of network performance degradation, and some high-importance stations within the lines act as catalysts to accelerate the performance degradation. The proposed method not only offers a valuable reference for quantifying network vulnerability arising from fluctuations in passenger mobility but also introduces a novel vulnerability evaluation index to the URT system.