Development of Intelligent Transport Systems: Digital Twins in the Railway Industry

Denis V. Zuev

doi:10.20295/2413-2527-2025-444-33-46

UDC

656.2 004.942

VAK Russia

2.9.8 1.2.2 2.3.6

DEVELOPMENT OF INTELLIGENT TRANSPORT SYSTEMS: DIGITAL TWINS IN THE RAILWAY INDUSTRY Development of Intelligent Transport Systems: Digital Twins in the Railway Industry

АА Аа

Published in Intellectual Technologies on Transport · Pages 33–46 · Rubric: ARTIFICIAL INTELLIGENCE AND TRANSPORT SYSTEMS

DOI: https://doi.org/10.20295/2413-2527-2025-444-33-46 · EDN: BJMGDY

Received: 21.10.2025 Accepted: 08.11.2025 Published: 15.12.2025

Authors

Denis V. Zuev

Academic degree: candidate of technical sciences

Sintez AT LLC General Director · Russian Federation

ABSTRACT

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.

KEYWORDS

intelligent transport systems, digital twin, railway infrastructure, BIM modelling, predictive maintenance, artificial intelligence, reliability, efficiency

1. GOST R 56829—2015. Intellektualnye transportnye sistemy. Terminy i opredeleniya [GOST R 56829—2015. Intelligent transport systems. Terms and definitions]. Effective from June 01, 2016. Moscow, StandartInform Publishing House, 2016, 13 p. (In Russian)

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, April 23–26, 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. Published online at July 01, 2021. Available at: http://www.globalrailwayreview.com/article/120887/ digital-twins-rail (accessed: September 28, 2025).

4. Rail Strategic Research and Innovation Agenda — December 2020, European Rail Research Advisory Council. Published online at December 01, 2020. Available at: http://errac.org/publications/rail-strategic-research-and-innovation-agenda-december-2020 (accessed: September 28, 2025).

5. Digital Modelling Workshop. 30 June 2021. Webinar Slidepack, International Union of Railways. Available at: http://uic.org/events/digital-modelling-workshop (accessed: September 28, 2025).

6. Magnien A., Janssen B., Dessagne G., Tane P. The Case for a Federated Digital Model of the Rail System, Global Railway Review. Published online at October 20, 2022. Available at: http://www.globalrailwayreview.com/article/138386/the-case-for-a-federated-digital-model-of-the-rail-system (accessed: September 28, 2025).

7. Crisan O. Italferr’s AI-Powered Digital Twin for Serravalle Tunnel, Bentley’s Blog. Published online at October 23, 2025. Available at: http://blog.bentley.com/software/yii-winner-bridges-and-tunnels-category-italferr-s-p-a (accessed: October 25, 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. EDN: https://elibrary.ru/TBZBLZ

9. China Mobile and ZTE Achieve Industry’s First Digital Twin-Based Precise Network Planning for High-Speed Rail, ZTE Official Website. Published online at November 10, 2023. Available at: http://www.zte.com.cn/global/about/news/china-mobile-and-zte-achieve-industrys-first-digital-twin-based-precise-network-planning-for-high-speed-rail (accessed: September 28, 2025).

10. Kadik L. Tsifrovye dvoyniki na zheleznoy doroge. K 2030 godu iskusstvennyy intellekt budet upravlyat transportnoy infrastrukturoy [Digital Twins on the Railway. By 2030, Artificial Intelligence Will Manage Transport Infrastructure], Gudok.RU. Published online at October 21, 2021. Available at: http://gudok.ru/content/analitika/infrastructure/1583619/ (accessed: September 28, 2025). (In Russian)

11. Olgeyzer I. A. Tsifrovoy dvoynik sortirovochnoy gorki [Digital Twin Sorting Yard], Avtomatika, svyaz, informatika [Automation, Communications, Informatics], 2020, No. 1, Pp. 20–22. DOI:https://doi.org/10.34649/AT.2020.1.1.003. (In Russian) DOI: 10.34649/АТ.2020.1.1.003; EDN: https://elibrary.ru/SZRZSK

12. “Umnyy lokomotiv” uvelichit proizvoditelnost depo na 22 % [“Smart Locomotive” to Increase Depot Productivity by 22 %], RZhD Tsifrovoy [RZD.Digital]. Published online at July 08, 2022. Available at: http://rzddigital.ru/projects/umnyy-lokomotiv-uvelichit-proizvoditelnost-depo-na-22/ (accessed: September 28, 2025). (In Russian)

13. Ob ustanovlenii sluchaev, pri kotorykh zastroyshchikom, tekhnicheskim zakazchikom, litsom, obespechivayushchim ili osushchestvlyayushchim podgotovku obosnovaniya investitsiy, i (ili) litsom, otvetstvennym za ekspluatatsiyu obekta kapitalnogo stroitelstva, obespechivayutsya formirovanie i vedenie informatsionnoy modeli obekta kapitalnogo stroitelstva [On establishing cases in which the developer, technical customer, person ensuring or carrying out the preparation of investment justification, and (or) the person responsible for the operation of a capital construction project ensure the formation and maintenance of an information model of the capital construction project]: Decree of the Government of the Russian Federation No. 331 dated March 05, 2021 (as amended on December 20, 2022 No. 2357). (In Russian)

GOST

Zuev D. V. Development of Intelligent Transport Systems: Digital Twins in the Railway Industry // . 2025. pp. 33-46. DOI: https://doi.org/10.20295/2413-2527-2025-444-33-46. EDN: BJMGDY. (Date of access 19.08.2026).

MLA

Denis V. Zuev. "Development of Intelligent Transport Systems: Digital Twins in the Railway Industry." (2025): 33-46. DOI: https://doi.org/10.20295/2413-2527-2025-444-33-46. EDN: BJMGDY.

APA

Zuev D. V. (2025). Development of Intelligent Transport Systems: Digital Twins in the Railway Industry. , 33-46. https://doi.org/10.20295/2413-2527-2025-444-33-46 EDN: BJMGDY.

Chicago

Denis V. Zuev. "Development of Intelligent Transport Systems: Digital Twins in the Railway Industry." , no. (2025): 33-46. https://doi.org/10.20295/2413-2527-2025-444-33-46. EDN: BJMGDY.

WIKI

{{cite journal | author = Zuev D. V. | title = Development of Intelligent Transport Systems: Digital Twins in the Railway Industry | journal = | year = 2025 | pages = 33-46 | doi = 10.20295/2413-2527-2025-444-33-46 }} EDN: BJMGDY

Copy

Export: BibTeX EndNote RefMan RusMARC

DEVELOPMENT OF INTELLIGENT TRANSPORT SYSTEMS: DIGITAL TWINS IN THE RAILWAY INDUSTRY Development of Intelligent Transport Systems: Digital Twins in the Railway Industry

Confirmation