Research on Passenger Flow Congestion Propagation of Multi-Level Rail Transit Considering Stopping Scheme

Due to the complex operational characteristics of multi-level rail transit networks, such as cross-system and multi-level, passenger flow congestion must not only consider the steady state of homogeneous transportation networks but also reveal the deep-seated mechanism of congestion spreading between heterogeneous transportation networks. An analysis theory of travel paths based on Improved Prospect Theory (IPT) is proposed using generalized travel time and congestion degree as dual reference points. By organically integrating passenger travel modes and routes, a two-layer model of passenger travel mode selection based on Nested Logit-Improved Prospect Theory (NL-IPT) is constructed. On this basis, considering key influencing factors such as the stopping scheme, an improved Susceptible-Infected-Recovered (SIR) model of multi-level rail transit passenger flow congestion propagation under bounded rationality conditions is proposed. Taking the multi-level rail transit in Beijing, China, as an example, the propagation process of passenger flow congestion in multi-level rail transit is simulated and analyzed. Through the sensitivity analysis of critical factors such as gain and loss sensitivity coefficient, propagation rate, and recovery rate, the mechanism of the influence of key parameters on passenger flow congestion propagation is revealed. The results show that when the proportion of waiting passengers heading to subsequent stops of the arriving train is greater than or equal to 0.6, there will be slight fluctuations in the initial stage of congestion propagation. When this proportion decreases by 80%, the congestion propagation range decreases by 23.3%. The research provides a reference for the operation plans and management optimization of multi-level rail transit.