Intelligent Energy-Efficient Train Trajectory Optimization Approach Based on Supervised Reinforcement Learning for Urban Rail Transits

Intelligent Energy-Efficient Train Trajectory Optimization Approach Based on Supervised Reinforcement Learning for Urban Rail Transits

Artificial intelligence of things (AIoT)-enabled intelligent automatic train operation (iATO) is an urgently needed technology to expand the capability of ATO in addressing the real-time responsiveness and dynamic online challenges to energy-efficient train trajectory optimization (TTO) and its asso...

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Bibliographic Details
Main Authors: Guannan Li, Siu Wing Or, Ka Wing Chan
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
energy-efficient train trajectory optimization
intelligent automatic train operation
supervised reinforcement learning
urban rail transits
Online Access:https://ieeexplore.ieee.org/document/10081361/

Internet

https://ieeexplore.ieee.org/document/10081361/

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