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Railway infrastructure maintenance efficiency improvement using deep reinforcement learning integrated with digital twin based on track geometry and component …
J Sresakoolchai, S Kaewunruen - Scientific reports, 2023 - nature.com
Railway maintenance is a complex and complicated task in the railway industry due to the
number of its components and relationships. Ineffective railway maintenance results in …
number of its components and relationships. Ineffective railway maintenance results in …
Artificial intelligence applied on traffic planning and management for rail transport: a review and perspective
J Zhang, J Zhang - Discrete Dynamics in Nature and Society, 2023 - Wiley Online Library
Artificial intelligence (AI) has received much attention in the domain of railway traffic
planning and management (TPM) from academia and industries. While many promising …
planning and management (TPM) from academia and industries. While many promising …
Integrated train timetabling and rolling stock rescheduling for a disturbed metro system: A hybrid deep reinforcement learning and adaptive large neighborhood search …
B Su, A D'Ariano, S Su, X Wang, T Tang - Computers & Industrial …, 2023 - Elsevier
For a metro line with high density and short trip time, the original train timetable and rolling
stock circulation face infeasible risks under unexpected disturbances. This paper focuses on …
stock circulation face infeasible risks under unexpected disturbances. This paper focuses on …
Reinforcement learning for online dispatching policy in real-time train timetable rescheduling
Train Timetable Rescheduling (TTR) is a crucial task in the daily operation of high-speed
railways to maintain punctuality and efficiency in the presence of unexpected disturbances …
railways to maintain punctuality and efficiency in the presence of unexpected disturbances …
Parallel dispatching: An ACP-based high-speed railway intelligent dispatching system
The antiquated method of train dispatching relying solely on dispatchers' knowledge is
unable to meet the need for rapid response and effective solutions in emergency situations …
unable to meet the need for rapid response and effective solutions in emergency situations …
Train traffic control in merging stations: A data-driven approach
Railway operations are subject to deviations from the planned schedule, ie, delays. In those
situations, high-quality traffic control actions are needed to reduce the delays. Existing …
situations, high-quality traffic control actions are needed to reduce the delays. Existing …
Integrated rescheduling of train timetables and rolling stock circulation for metro line disturbance management: a Q-learning-based approach
Disturbance occurs inevitably on a metro line, resulting in train delays and low service
quality. To improve the efficiency of disturbance management, this article investigates the …
quality. To improve the efficiency of disturbance management, this article investigates the …
A review of real-time railway and metro rescheduling models using learning algorithms
M Jusup, A Trivella, F Corman - 21st Swiss Transport …, 2021 - research-collection.ethz.ch
Planning railway and metro systems includes the critical step of finding a schedule for the
trains. Although buffer times and running supplements are added to the schedule to make …
trains. Although buffer times and running supplements are added to the schedule to make …
[HTML][HTML] Interactive reinforcement learning innovation to reduce carbon emissions in railway infrastructure maintenance
J Sresakoolchai, S Kaewunruen - Developments in the Built Environment, 2023 - Elsevier
Carbon emission is one of the primary contributors to global warming. The global community
is paying great attention to this negative impact. The goal of this study is to reduce the …
is paying great attention to this negative impact. The goal of this study is to reduce the …
Deep reinforcement learning based dynamic optimization of bus timetable
G Ai, X Zuo, G Chen, B Wu - Applied Soft Computing, 2022 - Elsevier
Bus timetable optimization is a key issue to reduce operational cost of bus company and
improve the transit service quality. Existing methods optimize the timetable offline. However …
improve the transit service quality. Existing methods optimize the timetable offline. However …