Deep reinforcement learning with reference system to handle constraints for energy-efficient train control

DOI10.1016/j.ins.2021.04.088zbMath1530.93365OpenAlexW3162452620MaRDI QIDQ6092048

Yonghua Zhou, Mengying Shang, Hamido Fujita

Publication date: 23 November 2023

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2021.04.088

zbMATH Keywords

train controlenergy savingconstraint handlingdeep reinforcement learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Application models in control theory (93C95)

Cites Work

• Local energy minimization in optimal train control
• Review of energy-efficient train control and timetabling
• On an optimal control problem of train operation
• Dynamic coast control of train movement with genetic algorithm
• Unnamed Item

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