The formulation of the current limiting scheme of an urban rail transit network is a complex multi-objective planning problem as the effect of the current limiting scheme is unknown before implementation. In this article, a method combining discrete event simulation and agent simulation is used to study the simulation scheduling principle of the current limiting scheme, and a modeling method based on an abstract agent group is proposed. Based on the AnyLogic simulation platform, a meso-scale simulation model for evaluating the current limiting scheme of urban rail transit networks was developed, and a logical framework for the operation simulation of the intelligent group and urban rail network system with stations, passengers, and trains as units was constructed. Furthermore, the data exchanges between stations, trains, and passengers were controlled through discrete events of driving. The results show that the constructed simulation model can effectively replace the actual system to evaluate the current limiting scheme and reduce the computational redundancy of passenger agents flowing in the urban rail network system and the cost of model transformation.