Konferensartikel

With the booming travel demands in megacities, the limited transportation capacity hasn’t satisfied them in urban rail transit. Passenger congestion problem become increasingly serious, which causes the potential accident risks on platforms. To further efficiently improve the conditions, this paper proposes an effective collaborative optimization method for the accurate passenger flow control strategies on an oversaturated urban rail transit line by simultaneously adjusting the number of inbound passengers entering multiple stations on the line. Through considering the space-time dynamic characteristics of passenger flow, a multi-objective integer linear programming model is formulated to minimize the number of passengers who are limited to enter stations, minimize the total passenger waiting time on platforms at all of involved stations where the optimal passenger flow control is imposed and maximize the passenger person-kilometres. And it is solved by CPLEX solver efficiently. Moreover, the passenger flow demands are time-variant, so it’s very necessary for the accurate and easy-to-implement passenger flow control strategies to determinate the control time intervals. Hence, this paper develops a method based on Fisher optimal division to get an optimal determination of the control time intervals before solving the model. Finally, two sets of numerical experiments, including a small-scale case and a real-world instance with operation data of Chengdu metro system, are implemented to demonstrate the performance and effectiveness of the proposed approach.

Urban rail transport, Passenger flow control, Multi-station coordination, Fisher optimal division method