Abstract:

To respond and alleviate the sudden large passenger flow of metro lines in time, a subway passenger flow control optimization model was proposed. Firstly, with the goals of minimizing the total waiting time of passengers and maximizing passenger flow through the interval, permitted inbound passenger flow was used as a decision-making variable to propose a RDM considering constraints such as the supply side, demand side, and passenger flow control intensity. Moreover, the volatility of passenger flow demand was analyzed, and a RM was developed by combining robust optimization theory. The volatility of passenger flow demand was analyzed, and an RM was developed combined with robust optimization theory. Secondly, the robust equivalent transformation theory was used to linearize the nonlinear constraints in RM and solved by the Lingo optimization solver. Finally, a metro line was taken as an example for analysis and verification. The results showed that the RDM model using capacity balance coefficients to decide the permissible inbound passenger flow effectively alleviated the pressure of passenger congestion and improved the efficiency of interval transport. When dealing with uncertain passenger demand, robustness coefficients were introduced in the RM model to adjust fluctuations range of passenger flow demand, thereby reducing the aggregation passenger flow risk and improving the reliability of the passenger flow control scheme.

Key words: sudden large passenger flow, metro systems, passenger flow control, optimization model, refined deterministic model (RDM), robust model (RM)