A Timetable Optimization Method for Urban Train Transit Based on Virtual Coupling
To solve the mismatch between train capacity and demand during peak hours,a timetable optimization method for urban train transit based on virtual coupling technical is proposed,incorporating spatiotemporal charac-teristics of passenger flow,oversaturation of trains during peak hours,and the limitation of the number of rolling stocks.A dynamic passenger flow cumulative demand(PFCD)function is proposed to pedict the passenger flow at different hours.Then,the schedule optimization model for urban rail transit based on the virtual coupling is estab-lished,in which,the departure time of trains at the first station and the marshaling scheme of each train are decision variables and the average waiting time(AWT)of passengers and the train travel mileage(TTM)are minimized un-der constraints such as passenger demand in different hours,departure interval,running time,number of rolling stocks,rolling stock circulation,etc.Lagrangian relaxation is introduced to reduce the complexity of the problem by absorbing the coupling constraints into the objective,and the original problem is decomposed into two independent subproblems.By using a commercial solver and the designed heuristic algorithm,the lower bound and upper bound of the problems are found.A metro line in Shanghai Metro is employed for demonstration,and the results show that:①the proposed dynamic PFCD function fits the arrival pattern of passengers well during the peak hours;②com-pared with the uniform departure schedule,the non-uniform departure(non-UD)schedule under the fixed train com-position(FTC)mode can reduce the AWT of passengers by 24.15% and the waiting time of stranded passengers by 51.73%;③compared with the non-UD schedule under the FTC mode,the train timetable based on virtual coupling can reduce not only the train running kilometers by 0.33% but also the AWT of passengers and the waiting time of stranded passengers by 16.95% and 6.03%,respectively.
万方数据
维普
