Optimal Design of Train Schedule of Urban Rail Transit Based on Time-varying Demand

In order to improve the market competitiveness of urban rail transit and make train timetables better serve passengers, the problem of train timetable optimization under time-varying passenger demand is studied. The cubic spline interpolation method is used to fit the passenger flow demand function, and then the obtained results are applied to the train timetable optimization model that minimizes the weighted sum of passenger waiting time, total train running time, and number of trains. Use simulated annealing algorithm to solve. Taking Xi'an Metro Line 2 as an example for analysis, the results show the feasibility of the model and algorithm.