Joint optimization of train scheduling and dynamic passenger flow control strategy with headway-dependent demand
Document Type
Journal Article
Publication Date
2022
Subject Area
place - asia, place - urban, mode - rail, mode - subway/metro, operations - scheduling, operations - frequency, ridership - demand
Keywords
Joint optimization, train scheduling, passenger flow control, headway-dependent demand
Abstract
Focusing on massive demand and high-frequency trains in urban rail transit, this paper proposes a novel joint optimization approach for train scheduling and dynamic passenger flow control strategy under oversaturated conditions to minimize the total number of waiting passengers. In view of the relationship between the number of boarding/alighting passengers and the dwell time of trains, the problem is formulated as a mixed-integer linear programming (MILP) model. This model can achieve the trade-off between the utilization of trains and passengers. The ILOG CPLEX is adopted to solve the proposed model. And a real-world case study of the Beijing Metro Line 5 is given to demonstrate the feasibility and effectiveness. Through jointly optimizing train schedule and flow control, the average boarding rate of passengers increases from 36.34% to 87.55%. The results show that the proposed flow control is effective in alleviating the oversaturated situations at platforms and trains.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Yuan, F., Sun, H., Kang, L., & Zhang, S. (2022). Joint optimization of train scheduling and dynamic passenger flow control strategy with headway-dependent demand. Transportmetrica B: Transport Dynamics, Vol. 10(1), pp. 627-651.
