Timetable Coordination of the First Trains for Subway Network With Maximum Passenger Perceived Transfer Quality

Non-coordinated first-train timetables can result in unfavorable train connections among different subway lines at transfer stations and generate rather long waiting time for transfer passengers. This paper aims at optimizing the first train originating times of different transit lines at the network scale. The cost function of transfer waiting time is formulated to evaluate the perceived transfer quality with the consideration of passengers' psychological feelings. The first-train timetable coordination model is then developed by minimizing the total waiting cost of passengers transferring between two first trains of different lines. The genetic algorithm is applied to solve the model. Finally, a case study from part of the Beijing subway network is conducted to verify the method. The results show that the total waiting cost of first-train transfer passengers is reduced by 49.67% with the application of our proposed model. Meanwhile, the number of super-long waiting is significantly reduced.