Urban Rail Train Diagram Compilation for Unbalanced Passenger Flow

Train diagram is an important basis for train operation and a decisive condition to ensure the safe and efficient travel of passengers. In view of the unbalanced characteristics of passenger flow in the morning commute, the train operation plan is formulated in combination with multi-routing mode, fast-slow mode and dynamic stop mode. The model is constructed to compile the train diagram with the goal of minimizing the average overload rate of the train, the average waiting time of the passengers and the travel distance of the train. The bi-level optimization algorithm is used, and the lower simulation is nested in the upper genetic algorithm to solve the model. The feasibility of the model and algorithm is verified by the actual data of Beijing Metro Line 6. The experimental results show that the mode of combining multi-routing with fast-slow train and dynamic parking reduces the average overload rate of trains and the average waiting time of passengers by 31.6% and 43.7% respectively. The method in this paper effectively improves the dynamic matching degree between the train diagram and the disequilibrium passenger flow, and meanwhile ensures the safe and efficient travel of passengers.