Train scheduling with deep Q-network: A feasibility test

I Gong, S Oh, Y Min - Applied Sciences, 2020 - mdpi.com
We consider a train scheduling problem in which both local and express trains are to be
scheduled. In this type of train scheduling problem, the key decision is determining the …

Reinforcement Learning for Scalable Train Timetable Rescheduling With Graph Representation

P Yue, Y Jin, X Dai, Z Feng… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Train timetable rescheduling (TTR) aims to promptly restore the original operation of trains
after unexpected disturbances or disruptions. Currently, this work is still done manually by …

When Mining Electric Locomotives Meet Reinforcement Learning

Y Li, Z Zhu, X Li, C Yang, H Lu - arXiv preprint arXiv:2311.08153, 2023 - arxiv.org
As the most important auxiliary transportation equipment in coal mines, mining electric
locomotives are mostly operated manually at present. However, due to the complex and …

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 …

Deep Q-Network approach for train timetable rescheduling based on alternative graph

KM Kim, HL Rho, BH Park, YH Min - Applied Sciences, 2023 - mdpi.com
The disturbance of local areas with complex railway networks and high traffic density not
only impedes the efficient use of rail networks in those areas, but also propagates delays to …

A Real‐Time Train Timetable Rescheduling Method Based on Deep Learning for Metro Systems Energy Optimization under Random Disturbances

J Liao, F Zhang, S Zhang… - Journal of Advanced …, 2020 - Wiley Online Library
Considering that uncertain dwell disturbances often occur at metro stations, researchers
have proposed many methods for solving the train timetable rescheduling (TTR) problem …

Adaptive railway traffic control using approximate dynamic programming

T Ghasempour, B Heydecker - Transportation Research Procedia, 2019 - Elsevier
This study presents an adaptive railway traffic controller for real-time operations based on
approximate dynamic programming (ADP). By assessing requirements and opportunities …

[HTML][HTML] Solving the train dispatching problem via deep reinforcement learning

V Agasucci, G Grani, L Lamorgese - Journal of Rail Transport Planning & …, 2023 - Elsevier
Every day, railways experience disturbances and disruptions, both on the network and the
fleet side, that affect the stability of rail traffic. Induced delays propagate through the network …

An Integrated Framework Integrating Monte Carlo Tree Search and Supervised Learning for Train Timetabling Problem

F Yang - arXiv preprint arXiv:2311.00971, 2023 - arxiv.org
The single-track railway train timetabling problem (TTP) is an important and complex
problem. This article proposes an integrated Monte Carlo Tree Search (MCTS) computing …

A real‐time timetable rescheduling method for metro system energy optimization under dwell‐time disturbances

G Yang, J Wang, F Zhang, S Zhang… - Journal of Advanced …, 2019 - Wiley Online Library
Automatic Train Systems (ATSs) have attracted much attention in recent years. A reliable
ATS can reschedule timetables adaptively and rapidly whenever a possible disturbance …