This paper aims to make passenger flow control strategies in a station or a line during peak hours to cooperate traffic supply with demand. A new passenger flow control model is proposed to determine which station should be controlled according to different characteristics of passenger flow in a line. The new model is a dynamic optimization model considering the number of inbound and transfer passengers in a station as the decision variable, the minimum travel time of passengers as the objective function, and the capacity of stations and trains as the constraint. Moreover, the passenger flow evolution on the urban rail transit system is also considered in the model. Genetic algorithm is introduced to solve this model. Finally, a real-world case is proposed to examine the validity of the proposed model.

urban rail transit; passenger flow control; dynamic control; discrete event evolution; genetic algorithm