inttransИнтеллектуальный транспортIntelligent transport3033-6007АО «НИИАС»inttrans-20Research ArticleОБЗОРНЫЕ РАБОТЫНаучный обзор: технологии высоких скоростей в железнодорожном транспортеScientific review: high-speed technologies in railway transportАлиевВ. А.AliyevV. A.

Алиев Вугар Амирович, д.ф.-м.н., профессор

Баку

Vugar A. Aliyev, Doctor of Physical and Mathematical Sciences, Professor

Baku

prof.vugar.aliyev@gmail.comОзеровА. В.OzerovA. V.

Озеров Алексей Валерьевич , Начальник Международного управления

Москва

Alexey V. Ozerov, Head of the International Department

Moscow

a.ozerov@vniias.ruБочковА. В.BochkovA. V.

Бочков Александр Владимирович , д.т.н., учёный секретарь

Москва

Alexander V. Bochkov, Doctor of Technical Sciences, Scientific Secretary

Moscow

a.bochkov@vniias.ruИнститут физики Министерства науки и образования; AMIR Technical Services CompanyАзербайджанInstitute of Physics, Ministry of Science and Education; AMIR Technical Services CompanyAzerbaijanАО «НИИАС»РоссияJSC «NIIAS»Russian Federation20251109202603(35)5466Copyright © Алиев В.А., Озеров А.В., Бочков А.В., 20262026Алиев В.А., Озеров А.В., Бочков А.В.Aliyev V.A., Ozerov A.V., Bochkov A.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.intelligent-transport.ru/jour/article/view/20

В статье представлен комплексный анализ современных тенденций развития высокоскоростного железнодорожного транспорта (ВСМ) в Китае, основанный на материалах XII Всемирного конгресса по высокоскоростным железным дорогам (Пекин, 2025). Рассматриваются ключевые технологические достижения, включая создание инновационного подвижного состава серии CR450 с рекордной скоростью 450 км/ч, внедрение интеллектуальных систем управления (CTCS) и переход на связь нового поколения (5G-R). Особое внимание уделено цифровой трансформации отрасли: применению искусственного интеллекта для диагностики и прогнозирования, созданию цифровых двойников инфраструктуры, а также масштабной роботизации процессов обслуживания. Анализируется роль Китайской академии железнодорожных наук (CARS) как системообразующего элемента национальной инновационной экосистемы, обеспечивающей полный цикл разработки от фундаментальных исследований до промышленного внедрения. Подчеркивается значение государственной стратегии, сочетающей масштабные инвестиции в НИОКР, развитие испытательной базы и активную патентную защиту технологий. Статья будет полезна специалистам в области транспортного машиностроения, железнодорожной автоматики и цифровых технологий, а также представителям органов управления транспортной отраслью, интересующимся передовым международным опытом.

The article provides a thorough analysis of the latest developments in China’s high-speed rail (HSR) sector, drawing from materials presented at the 12th World Congress on High-Speed Rail in Beijing in 2025. The article examines key technological achievements, such as the development of the innovative CR450 series of trains capable of reaching speeds of up to 450 km/h, the implementation of intelligent control systems (CTCS), and the shift towards next-generation communications technology (5G-R). Particular attention is given to the industry’s digital transformation, including the use of artificial intelligence for diagnostics and forecasting, creating digital twins of infrastructure, and large-scale robotization of maintenance processes. The article analyzes the role of the Chinese Academy of Railway Sciences (CARS) as a system-forming element of the national innovation ecosystem that provides a full development cycle from fundamental research to industrial implementation. The importance of a state strategy that combines large-scale investment in research and development (R&D), the development of a testing base, and active patent protection of technologies is emphasized. This article is useful for specialists in transport engineering, railway automation, and digital technologies, as well as for transport industry management representatives interested in advanced international experience.

высокоскоростной железнодорожный транспортискусственный интеллектцифровизациясистемы управления движениемкитайские железные дорогиCR450CTCS5G-RCARShigh-speed rail transportartificial intelligencedigitalizationtraffic control systemsChinese railwaysCR450CTCS5G-RCARSReferencesZhou, M., Peng, Y., & An, L. (2022). Technical advances, innovation and challenges of developing high-speed rail in China. Proceedings of the Institution of Civil Engineers. https://doi.org/10.1680/jcien.21.00149Zhou, M., Peng, Y., & An, L. (2022). Technical advances, innovation and challenges of developing high-speed rail in China. Proceedings of the Institution of Civil Engineers. https://doi.org/10.1680/jcien.21.00149Feng, L., & Yu, X. (2018). A Study on the Integration Innovation Mode of China Railway High-Speed (CRH) Technology. Portland International Conference on Management of Engineering and Technology. https://doi.org/10.23919/PICMET.2018.8481875Feng, L., & Yu, X. (2018). A Study on the Integration Innovation Mode of China Railway High-Speed (CRH) Technology. Portland International Conference on Management of Engineering and Technology. https://doi.org/10.23919/PICMET.2018.8481875Fang, X., Yang, Z., & Lin, F. (2013). Virtual Development Platform of High-Speed Train Traction Drive System in View of Top-Level Goals. Vehicle Power and Propulsion Conference. https://doi.org/10.1109/VPPC.2013.6671741Fang, X., Yang, Z., & Lin, F. (2013). Virtual Development Platform of High-Speed Train Traction Drive System in View of Top-Level Goals. Vehicle Power and Propulsion Conference. https://doi.org/10.1109/VPPC.2013.6671741Hao, W. (2012). Development of the High Speed Comprehensive Inspection TrainHao, W. (2012). Development of the High Speed Comprehensive Inspection TrainJi, P. (2023). Head shape design of Chinese 450 km/h high-speed trains based on pedigree feature parameterization. https://doi.org/10.21606/iasdr.2023.231Ji, P. (2023). Head shape design of Chinese 450 km/h high-speed trains based on pedigree feature parameterization. https://doi.org/10.21606/iasdr.2023.231Oh, K. T., Yoo, M.-S., Jin, N., Ko, J., Seo, J., Joo, H., & Ko, M. (2022). A Review of Deep Learning Applications for Railway Safety. Applied Sciences. doi: 10.3390/app122010572Oh, K. T., Yoo, M.-S., Jin, N., Ko, J., Seo, J., Joo, H., & Ko, M. (2022). A Review of Deep Learning Applications for Railway Safety. Applied Sciences. doi: 10.3390/app122010572Liu, J., Liu, G., Wang, Y., & Zhang, W. (2024). Artificial-intelligent-powered safety and efficiency improvement for integrated railway systems. High-speed railway. doi: 10.1016/j.hspr.2024.06.006Liu, J., Liu, G., Wang, Y., & Zhang, W. (2024). Artificial-intelligent-powered safety and efficiency improvement for integrated railway systems. High-speed railway. doi: 10.1016/j.hspr.2024.06.006Liu, J., Liu, G., Wang, Y., & Zhang, W. (2024). Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems. High-speed railway. doi: 10.1016/j.hspr.2024.06.002Liu, J., Liu, G., Wang, Y., & Zhang, W. (2024). Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems. High-speed railway. doi: 10.1016/j.hspr.2024.06.002Yan, Z., Tiantian, W., JingSong, Y., & Guoqin, Z. (2023). Development and engineering application of integrated safety monitoring system for China’s high-speed trains. Transportation safety and environment. doi: 10.1093/tse/tdad017Yan, Z., Tiantian, W., JingSong, Y., & Guoqin, Z. (2023). Development and engineering application of integrated safety monitoring system for China’s high-speed trains. Transportation safety and environment. doi: 10.1093/tse/tdad017Yi, S., Kuang, J., & Liu, R. (2023). Research on Safety Risk Prediction Model of High-Speed Railway Based on Chaotic RBF Neural Network. Journal Article. doi: 10.1109/ishc61216.2023.00025Yi, S., Kuang, J., & Liu, R. (2023). Research on Safety Risk Prediction Model of High-Speed Railway Based on Chaotic RBF Neural Network. Journal Article. doi: 10.1109/ishc61216.2023.00025Zihui, Z., Tian, X., & Zhiwei, S. (2023). Deepening Research on the Comprehensive Application and Development of Railway Intelligent Detection and Monitoring System and Key Technologies. Journal Article. https://doi.org/10.1109/itoec57671.2023.10291609Zihui, Z., Tian, X., & Zhiwei, S. (2023). Deepening Research on the Comprehensive Application and Development of Railway Intelligent Detection and Monitoring System and Key Technologies. Journal Article. https://doi.org/10.1109/itoec57671.2023.10291609Zheng, Song, Xu, Lei. (2020). A Fault Diagnosis Method of Bogie Axle Box Bearing Based on Spectrum Whitening Demodulation. Sensors (Basel, Switzerland). doi: 10.3390/s20247155Zheng, Song, Xu, Lei. (2020). A Fault Diagnosis Method of Bogie Axle Box Bearing Based on Spectrum Whitening Demodulation. Sensors (Basel, Switzerland). doi: 10.3390/s20247155Sai, D. H. (2024). Revolutionizing Railways: An AI-Powered Approach for Enhanced Monitoring and Optimization. Journal Article. doi: 10.55041/isjem01382Sai, D. H. (2024). Revolutionizing Railways: An AI-Powered Approach for Enhanced Monitoring and Optimization. Journal Article. doi: 10.55041/isjem01382Miao, Z., Zhang, Q., Lv, Y., Wenzhe, S., & Wang, H. (2018). An AI based High-speed Railway Automatic Train Operation System Analysis and Design. Proceedings Article. doi: 10.1109/ICIRT.2018.8641650Miao, Z., Zhang, Q., Lv, Y., Wenzhe, S., & Wang, H. (2018). An AI based High-speed Railway Automatic Train Operation System Analysis and Design. Proceedings Article. doi: 10.1109/ICIRT.2018.8641650Li, X., Zhu, M., Zhang, B., Wang, X., Liu, Z. A., & Han, L. (2024). A review of artificial intelligence applications in high-speed railway systems. High-speed railway. doi: 10.1016/j.hspr.2024.01.002Li, X., Zhu, M., Zhang, B., Wang, X., Liu, Z. A., & Han, L. (2024). A review of artificial intelligence applications in high-speed railway systems. High-speed railway. doi: 10.1016/j.hspr.2024.01.002Sai, D. H. (2024). Revolutionizing Railways: An AI-Powered Approach for Enhanced Monitoring and Optimization. Journal Article. doi: 10.55041/isjem01382Sai, D. H. (2024). Revolutionizing Railways: An AI-Powered Approach for Enhanced Monitoring and Optimization. Journal Article. doi: 10.55041/isjem01382Zihui, Z., Tian, X., & Zhiwei, S. (2023). Deepening Research on the Comprehensive Application and Development of Railway Intelligent Detection and Monitoring System and Key Technologies. Journal Article. doi: 10.1109/itoec57671.2023.10291609Zihui, Z., Tian, X., & Zhiwei, S. (2023). Deepening Research on the Comprehensive Application and Development of Railway Intelligent Detection and Monitoring System and Key Technologies. Journal Article. doi: 10.1109/itoec57671.2023.10291609Hong, P. (2017). Intelligent trouble diagnosis method for high-speed rail. Patent.Hong, P. (2017). Intelligent trouble diagnosis method for high-speed rail. Patent.Dubljanin, D., Marković, F., Dimić, G., Vučković, D., Petković, M., & Mosurović, L. (2024). Educational Application of Artificial Intelligence for Diagnosing the State of Railway Tracks. International Journal of Cognitive Research in Science, Engineering and Education.Dubljanin, D., Marković, F., Dimić, G., Vučković, D., Petković, M., & Mosurović, L. (2024). Educational Application of Artificial Intelligence for Diagnosing the State of Railway Tracks. International Journal of Cognitive Research in Science, Engineering and Education.Chien-Kuo Chiu. (2024). AI-Driven railway regulator inspection planning system: enhancing railway safety inspection prioritisation and incident management. HKIE Transactions. https://doi.org/10.33430/v31n4thie-2024-0012Chien-Kuo Chiu. (2024). AI-Driven railway regulator inspection planning system: enhancing railway safety inspection prioritisation and incident management. HKIE Transactions. https://doi.org/10.33430/v31n4thie-2024-0012

The authors declare that there are no conflicts of interest present.