UDC 004.942
An overview of the evolution of intelligent transport systems within the railway sector is presented, highlighting the pivotal role of “digital twins” technology for both infrastructure and rolling stock. The relevance of this topic arises from the ongoing global digital transformation within the railway industry, which aims to enhance the safety, reliability and efficiency of the transportation processes. Purpose: to conduct a comparative analysis of major projects, technological solutions and approaches to the implementation of digital twins in the European Union, China, and Russia, while also assessing their impact on operational performance. Methods: the analysis incorporates initiatives from the European Union, such as Shift2Rail and Europe’s Rail, which emphasize standardization and predictive maintenance; extensive Chinese government programmes such as the Digital Railway Plan set for completion by 2035, recognized for its emphasis on high speed and integrated technologies (such as BIM and 5G-R); and the pragmatic strategies adopted by Russian Railways (ACS BIM, the “Smart Locomotive”, and the digital twin of the marshalling yard), all aimed at achieving intelligent asset management by 2030. The findings indicate that all regions are utilizing a common technological foundation, encompassing BIM platforms, IoT/5G networks, AI/ML analytics, and simulation models. Results: the results demonstrate that digital twins facilitate early defect detection and predictive preventive maintenance, resulting in fewer accidents, increased reliability, reduced unplanned downtime by up to 30%, and improved economic efficiency, with maintenance costs reduced by up to 30% and operations optimized.
intelligent transport systems, digital twin, railway infrastructure, BIM modelling, predictive maintenance, artificial intelligence, reliability, efficiency
1. GOST R 56829—2015. Intellektual'nye transportnye sistemy. Terminy i opredeleniya = Intelligent transport systems. Terms and definitions: nacional'nyy standart Rossiyskoy Federacii: vveden v deystvie prikazom Federal'nogo agentstva po tehnicheskomu regulirovaniyu i metrologii ot 10 dekabrya 2015 g. № 2150-st: data vvedeniya: 2016-06-01. M.: Standartinform, 2016. 13 s.
2. Glaessgen E. H., Stargel D. S. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles // Proceedings of the 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference (Honolulu, HI, USA, 23–26 April 2012). American Institute of Aeronautics and Astronautics, 2012. 14 p. DOI:https://doi.org/10.2514/6.2012-1818.
3. Spanevello T. Digital Twins: Accelerating the Digital Transformation in the Rail Sector // Global Railway Review. 2021. 01 July. URL: http://www.globalrailwayreview.com/article/120887/digital-twins-rail (data obrascheniya: 28.09.2025).
4. Rail Strategic Research and Innovation Agenda — December 2020 // European Rail Research Advisory Council. 2020. 01 December. URL: http://errac.org/publications/rail-strategic-research-and-innovation-agenda-december-2020 (data obrascheniya: 28.09.2025).
5. Digital Modelling Workshop. 30 June 2021. Webinar Slidepack // International Union of Railways. URL: http://uic.org/ events/digital-modelling-workshop (data obrascheniya: 28.09.2025).
6. The Case for a Federated Digital Model of the Rail System / A. Magnien, B. Janssen, G. Dessagne, P. Tane // Global Railway Review. 2022. 20 October. URL: http://www.globalrailwayreview.com/article/ 138386/the-case-for-a-federated-digital-model-of-the-rail-system (data obrascheniya: 28.09.2025).
7. Crisan O. Italferr’s AI-Powered Digital Twin for Serravalle Tunnel // Bentley’s Blog. 2025. 23 October. URL: http://blog.bentley.com/software/yii-winner-bridges-and-tunnels-category-italferr-s-p-a (data obrascheniya: 25.10.2025).
8. Wang T. The Intelligent Beijing–Zhangjiakou High-Speed Railway // Engineering. 2021. Vol. 7, Iss. 12. Pp. 1665–1672. DOI:https://doi.org/10.1016/j.eng.2021.10.006.
9. China Mobile and ZTE Achieve Industry’s First Digital Twin-Based Precise Network Planning for High-Speed Rail // ZTE Official Website. 2023. 10 November. URL: http://www.zte.com.cn/global/about/news/china-mobile-and-zteachieveindustrys-first-digital-twin-based-precise-network-planning-for-high-speed-rail (data obrascheniya: 28.09.2025).
10. Kadik L. Cifrovye dvoyniki na zheleznoy doroge. K 2030 godu iskusstvennyy intellekt budet upravlyat' transportnoy infrastrukturoy // Gudok.RU. 2021. 21 oktyabrya. URL: http://gudok.ru/content/analitika/infrastructure/ 1583619/ (data obrascheniya: 28.09.2025).
11. Ol'geyzer I. A. Cifrovoy dvoynik sortirovochnoy gorki // Avtomatika, svyaz', informatika. 2020. № 1. S. 20–22. DOI:https://doi.org/10.34649/AT.2020.1.1.003.
12. «Umnyy lokomotiv» uvelichit proizvoditel'nost' depo na 22 % // RZhD Cifrovoy. 2022. 08 iyulya. URL: http://rzddigital.ru/projects/umnyy-lokomotiv-uvelichit-proizvoditelnost-depo-na-22/ (data obrascheniya: 28.09.2025).
13. Ob ustanovlenii sluchaev, pri kotoryh zastroyschikom, tehnicheskim zakazchikom, licom, obespechivayuschim ili osuschestvlyayuschim podgotovku obosnovaniya investiciy, i (ili) licom, otvetstvennym za ekspluataciyu ob'ekta kapital'nogo stroitel'stva, obespechivayutsya formirovanie i vedenie informacionnoy modeli ob'ekta kapital'nogo stroitel'stva: postanovlenie Pravitel'stva Rossiyskoy Federacii ot 05 marta 2021 goda № 331 (red. ot 20 dekabrya 2022 goda № 2357).
