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General review | Open Access

A review of artificial intelligence in train driving and control

Yunxiang Xie1Huachang Yang2( )
CARS Engineering Consulting Corporation Limited (Beijing), China Academy of Railway Sciences Corporation Limited, Beijing, China
Signal & Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
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Abstract

Purpose

In recent years, the rapid advancement of artificial intelligence (AI) has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector. Within the railway industry, AI has driven continuous upgrading and optimization of intelligent train control technology, thanks to its enhanced computational capabilities derived from advanced algorithms and models, as well as its role in improving safety performance. Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.

Design/methodology/approach

This paper, therefore, conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale. It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology, elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.

Findings

The application of AI technology in the train driving and control field is still in its infancy. While a large number of AI technologies have been widely adopted, there remains significant room for further optimization and improvement of these technologies. Additionally, a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.

Originality/value

The research findings provide references and guidance for advancing train control technology, promoting the digital transformation of railways, accelerating the overall optimization and upgrading of railway industry technologies, and facilitating the accelerated development of global railways.

References

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Railway Sciences
Pages 762-782

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Cite this article:
Xie Y, Yang H. A review of artificial intelligence in train driving and control. Railway Sciences, 2025, 4(6): 762-782. https://doi.org/10.1108/RS-09-2025-0036

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Received: 05 September 2025
Revised: 28 September 2025
Accepted: 30 September 2025
Published: 01 December 2025
© Yunxiang Xie and Huachang Yang. Published in Railway Sciences.

This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY 4.0 licence.