Joint optimization of modular vehicle schedule and fair passenger flow control under heterogeneous passenger demand in a rail transit system

With the rapid development of intelligent rail transit, fully automatic operation is progressively being achieved, and more approaches have appeared to enable operators to solve the supply–demand matching problem. Allowing advance reservations is one of the most efficient approaches under the novel “reservation and customization” operational logic. Passengers send trip requests via a reservation platform in real time, and operators plan the operational schedule based on the collected demand. To realize the operational pattern, we propose a trip reservation system (TRS) and introduce its architecture. To solve the trip reservation problem (TRP), a vehicle scheduling and passenger flow control (VSPFC) model is proposed. Using this model, the total cost of the system based on time and space capacity constraints is minimized, and the heterogeneity of passengers, fairness of passenger flow control and modular vehicle schedules are taken into consideration. A nested heuristic algorithm is applied to optimize the timetable and vehicle formation and obtain the passenger flow control plan, including feedback for reserved passengers. The Batong Line of the Beijing Subway is taken as a real-world case study to test the feasibility of the proposed model and algorithms. The results show that passenger travel efficiency can be improved as the number of reserved passengers increases. The passenger waiting time can be reduced and passenger flow can be controlled in a fair manner using the TRS proposed in this study, demonstrating its benefits over the flow control policies in a previous study.