@article{Song2026, 
author = {Shubao Song and Jingyu Zhang},
title = {Digital twin technology in railway infrastructure},
year = {2026},
journal = {Railway Sciences},
volume = {5},
number = {4},
pages = {505-523},
keywords = {Digital twin, Railway infrastructure, Predictive maintenance, IoT, Artificial intelligence, Cyber-physical systems},
url = {https://www.sciopen.com/article/10.1108/RS-02-2026-0013},
doi = {10.1108/RS-02-2026-0013},
abstract = {PurposeThis review aims to provide insights for researchers and practitioners to utilize the full potential of digital twins (DT) in railway infrastructure, furthermore, promoting the future advances of DT technology in the field.Design/methodology/approachThis paper comprehensively reviews the latest progress in the application of digital twins in railway infrastructure (Digital Twin for Railway Infrastructure (DTRI)). It systematically summarizes the application scenarios and elaborates on the core components of DTRI.FindingsThe core components of DTRI include virtual entity models, twin data, and virtual-physical connections. Emerging developments such as artificial intelligence (AI), data fusion, the Internet of Things (IoT) and advanced algorithms have been incorporated as the key technologies. The primary application scenarios focus on monitoring and maintenance, failure prediction and prevention and life cycle management.Originality/valueDT technology has emerged as an innovative framework in the railway infrastructure sector, offering unprecedented opportunities for real-time monitoring, predictive maintenance and optimization control. The paper analyzes current and future challenges alongside emerging development directions, highlighting the transformative potential of DT technology in promoting intelligent and efficient railway infrastructure operations.}
}