Study on the adaptability of multilayer subway network under sudden large passenger flow disturbances.

Abstract

This paper proposes a multilayer network-based subway network adaptability assessment framework.Adaptability is defined as the ratio of post-disturbance cumulative network performance to its nominal value, represented as 0≤ [Formula: see text]≤1. In this framework, each line is treated as a separate layer, with the introduction of composite edge weight and platform congestion factor, and the establishment a performance response function. By integrating the "physical accessibility-perceived impedance" flow diversion model and bond percolation theory, the framework characterizes failure propagation, and is verified using the Shanghai Metro regional network, with fair comparisons made against the weighted single-layer network (WSN) and the multigraph model (MLG). The results show that the critical threshold of the multilayer network is 12% and 11% higher than that of WSN and MLG, respectively; under severe attack, the network performance exceeds [Formula: see text] by 23%-33%, and ΔK is 22%-26% lower. Monte Carlo variance analysis further indicates a significant interaction (p < 0.01) between passenger flow arrival and route choice.