Novel approach to optimizing express–local metro train timetable considering multiple train stopping patterns
A traditional hybrid operational mode of a metro system usually combines the express and local trains. The stopping patterns of express trains are generally assumed to be the same. To provide a diverse service, this paper aims to explore the train timetable optimization method when the express trains have different stopping patterns. First, all the trains are categorized into five cases based on the type of train and the order of departure. A passenger-oriented timetabling model for reducing passenger waiting time is established, which can be solved by the Interior Point Method. Numerical examples from Guangzhou Metro Network are conducted with six scenarios, symbolizing different operation strategies. The proposed model was validated through numerical experiments conducted on a Nanjing metro line. The results indicate that the proposed model can efficiently reschedule the timetable in express/local mode with multiple stopping patterns and reduce the passenger waiting time, the most considerable reduction of which comes up to 16.8%, along with a reduction in their extra waiting time of up to 17.3%.
Authors
- Yuanwen Lai (ORCID: https://orcid.org/0000-0003-0722-5117)
- Said M. Easa (ORCID: https://orcid.org/0000-0003-0754-138X)
- Wenhai Lan
- Renjie Zhang (ORCID: https://orcid.org/0000-0003-0692-9550)
- Mao Ye (ORCID: https://orcid.org/0000-0002-8825-8326)
- Yuchao Zhan
Institutions
- Nanjing University of Science and Technology (CN)
- Southeast University (BD)
- Metropolitan University (RS)
- Guangzhou Metro Group (China) (CN)
- Fujian Petrochemical Group (China) (CN)
- Toronto Metropolitan University (CA)
- Southeast University (CN)
- Fuzhou University (CN)
- Ministry of Industry and Information Technology (CN)
Publication Details
- Journal
- Canadian Journal of Civil Engineering
- Published
- 2025-02-04
- DOI
- https://doi.org/10.1139/cjce-2024-0366
- Primary Topic
- Railway Systems and Energy Efficiency
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China