Joint optimization of train scheduling and dynamic passenger flow control strategy with 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.

KEYWORDS:

• Joint optimization
• train scheduling
• passenger flow control
• headway-dependent demand

Acknowledgments

The authors would like to thank the editor and two anonymous reviewers for their valuable comments and suggestions on the early version of this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Natural Science Foundation of China (Nos. 71771018, 72171020, 71890972/71890970, 72001017), the 111 Project (No. B20071), and the Fundamental Research Funds for the Central Universities (2019JBZ108).