Liu, J. orcid.org/0000-0002-3808-5957 and Liu, R. orcid.org/0000-0003-0627-3184 (2024) Schedule Extra Train(s) into Existing Timetable Using Actor-Critic Reinforcement Learning. In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 24-28 Sep 2023, Bilbao, Spain. IEEE , pp. 1166-1171. ISBN 979-8-3503-9947-9
Abstract
Train scheduling is a crucial part of railway operations, where trains are allocated to particular routes and times to ensure a sustainable utilization of the railway network. Decisions of train scheduling are usually made in well advanced after considering various factors such as expected passenger and freight demand, infrastructure availability, and operational constraints. Nonetheless, scheduling extra train services, being it for passengers or freight, to accommodate unexpected demand in the railway system remains a persistent challenge. This is due to the fact that the existing timetable is typically designed with predetermined robustness, and the introduction of additional trains can adversely impact the robustness of the timetable. To address this issue, this paper presents an approach using an actor-critic reinforcement learning algorithm that takes into account the aspect of timetable robustness in solving the problem of scheduling additional trains. A case study of this method demonstrates that the proposed algorithm can take into account the importance of robustness in the decision-making process, resulting in well-informed decisions and a more reliable timetable.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: | |
Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Built Environment and Design; Commerce, Management, Tourism and Services; Engineering; Transportation, Logistics and Supply Chains; Information and Computing Sciences; Civil Engineering; Urban and Regional Planning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Funding Information: | Funder Grant number Rail Safety & Standards Board Not Known |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Aug 2024 10:37 |
Last Modified: | 30 Aug 2024 13:33 |
Published Version: | https://ieeexplore.ieee.org/document/10422338 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/itsc57777.2023.10422338 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216424 |