Adaptive rail transit network operations with a rollout surrogate-approximate dynamic programming approach
This paper presents an adaptive optimization framework for dynamic rail transit network operations with use of a rollout surrogate-approximate dynamic programming method. The optimization algorithm derives coordinated decisions of service schedules and train unit deployment with respect to prevailing passenger demand. Considering the computational effectiveness needed for real-time applications, a state-dependent surrogate function is incorporated to approximate the costs associated with operational decisions over future stages. The surrogate approximation is updated iteratively via a temporal difference learning process with feeding of observations made from the transit network. The proposed framework is implemented and tested on a real-world scenario in Hong Kong Light Rail Transit (LRT) network. The results reveal that the proposed framework is able to reduce significantly the total passengers’ waiting times over existing plans with reasonable computational time via use of the surrogate approximation. This suggests the potential of the proposed optimizer for real time applications in large-scale rail transit networks.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
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Supplemental Notes:
- © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Nguyen, Hoa T M
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0000-0002-2932-3204
- Chow, Andy H F
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0000-0002-2877-357X
- Publication Date: 2023-3
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 104021
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Serial:
- Transportation Research Part C: Emerging Technologies
- Volume: 148
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0968-090X
- Serial URL: http://www.sciencedirect.com/science/journal/0968090X
Subject/Index Terms
- TRT Terms: Adaptive control; Light rail transit; Networks; Optimization; Schedules; Waiting time
- Geographic Terms: Hong Kong (China)
- Subject Areas: Operations and Traffic Management; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01875361
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 13 2023 10:23AM