Current state and predicted technological trends in global railway intelligent digital transformation

Author:

Li Ping,Xue RuiORCID,Shao Sai,Zhu YuhaoORCID,Liu YiORCID

Abstract

PurposeIn recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.Design/methodology/approachThis paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.FindingsDigital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.Originality/valueThe results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

Publisher

Emerald

Reference33 articles.

1. Japan’s model of mobile ecosystem success: The case of NTT DoCoMo;Journal of Emerging Knowledge on Emerging Markets,2011

2. Intelligent emergency management system for railway transport;Transportation Research Procedia,2021

3. From ccs-planning to testautomation: The digital testfield of deutsche bahn in scheibenberg-a case study,2021

4. A statistical study of railway safety in China and Japan 1990-2020;Accident Analysis and Prevention,2022

5. Fault diagnosis based on deep learning for current-carrying ring of catenary system in sustainable railway transportation;Applied Soft Computing,2021

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