Autors: Atanasov, I. I., Nenova, M. V., Pencheva E.
Title: On Some Aspects of Distributed Control Logic in Intelligent Railways
Keywords: automatic train protection, critical data communications, distributed intelligent control, railway transport, time constraints

Abstract: comfortable, reliable, safe and environmentally friendly high-speed train journey that saves time and offers an unforgettable experience for passengers is not a dream. Passengers can enjoy panoramic views, delicious cuisine and use their mobile devices without restrictions. High-speed trains, powered by environmentally friendly methods, are a sustainable form of transport, reducing harmful emissions. Integrating intelligent control and management into railway networks has the capacity to increase efficiency and improve reliability and safety, as well as reduce development and maintenance costs. Future intelligent railway network architectures are expected to focus on integrated, multi-layered systems that deeply embed artificial intelligence (AI), the Internet of Things (IoT) and advanced communication technologies (5G/6G) to ensure intelligent operation, improved reliability and increased safety. Distributed intelligent control in railways refers to an advanced approach in which decision-making capabilities are distributed across network components (trains, stations, track sections, control centers) rather than being concentrated in a single central location. The recent advances in AI in railways are associated with numerous scientific papers that enable intelligent traffic management, automatic train control, and predictive maintenance, with each of the proposed intelligent solutions being evaluated in terms of key performance indicators such as latency, reliability, and accuracy. This study focuses on how different intelligent solutions in railways can be implemented in network components based on the requirements for real-time control, near-real-time control, and non-real-time operation. The analysis of related works is focused on the proposed intelligent railway frameworks and architectures. The description of typical use cases for implementing intelligent control aims to summarize latency requirements and the possible distribution of control logic between network components, taking into account time constraints. The considered use case of automatic train protection aims to evaluate the added latency of communication. The requirements for the nodes that host and execute the control logic are identified.

References

  1. Europe’s Rail, System Pillar Consortium—Task 1, UIC and UNIFE. Energy Saving in Rail: Consumption Assessment, Efficiency Improvement and Saving Strategies, Overview Report 2024 Available online: https://share.google/xFUZWNw1G8UoVRMvF (accessed on 27 December 2025)
  2. García-Méndez S. de Arriba-Pérez F. Leal F. Veloso B. Malheiro B. Carlos Burguillo-Rial. J. An explainable machine learning framework for railway predictive maintenance using data streams from the metro operator of Portugal Sci. Rep. 2025 15 27495 10.1038/s41598-025-08084-1
  3. Shaikh M.Z. Ali S. Ali S. Baro E.N. Baloch Y.A. Chowdhry B.S. Predictive Maintenance in Urban Railway Systems Using Machine Learning Models Proceedings of the Global Conference on Wireless and Optical Technologies (GCWOT) Malaga, Spain 25–27 September 2024 1 5 10.1109/GCWOT63882.2024.10805699
  4. Nigam S. Kumar D. Mukherji S. Tomar S.S. Shastri S. Gupta P. Predictive Maintenance of Railway Tracks Using LSTM Proceedings of the IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies (INSPECT) Gwalior, India 7–8 December 2024 1 5 10.1109/INSPECT63485.2024.10896208
  5. Mario B. Mezhuyev V. Tschandi M. Predictive maintenance for Railway Domain: A systematic Literature Review IEEE Eng. Manag. Rev. 2023 51 120 140 10.1109/emr.2023.3262282
  6. Pasurangga D. Baltasar S. Data Driven Predictive Maintenance Framework for Railway Safety in Indonesia AJRI 2025 7 75 87
  7. Le-Nguyen M.-H. Turgis F. Fayemi P.-E. Bifet A. Real-time learning for real-time data: Online machine learning for predictive maintenance of railway systems Trans. Res. Proc. 2023 72 171 178 10.1016/j.trpro.2023.11.391
  8. Bianchi G. Fanelli C. Freddi F. Giuliani F. La Placa A. Systematic review railway infrastructure monitoring: From classic techniques to predictive maintenance Adv. Mech. Eng. 2025 17 1 26 10.1177/16878132241285631
  9. Tagiew R. Leinhos D. von der Haar H. Klotz C. Sprute D. Ziehn J. Schmelter A. Witte S. Klasek P. Sensor system for development of perception systems for ATO Discov. Artif. Intell. 2023 3 22 10.1007/s44163-023-00066-4
  10. Basile G. Napoletano E. Petrillo A. Santini S. Roadmap and challenges for reinforcement learning control in railway virtual coupling Discov. Artif. Intell. 2022 2 27 10.1007/s44163-022-00042-4
  11. Gozali A.A. Ruriawan M.F. Alamsyah A. Purwanto Y. Romadhony A. Wijaya F. Nugroho F. Husna D. Kridanto A. Fakhrudin A. et al. Smart train control and monitoring system with predictive maintenance and secure communications features Transp. Res. Interdiscip. Perspect. 2025 31 101409 10.1016/j.trip.2025.101409
  12. Sarp S. Kuzlu M. Jovanovic V. Polat Z. Guler O. Digitalization of railway transportation through AI-powered services: Digital twin trains Eur. Transp. Res. Rev. 2024 16 58 10.1186/s12544-024-00679-5
  13. Nagy A. Tick A. From Innovation to Implementation: Leveraging AI-Driven Automation in Smart Urban Railway Operations Proceedings of the IEEE 12th International Conference on Computational Cybernetics and Cyber-Medical Systems (ICCC) Mahe Island, Beau Vallon, Seychelles 9–11 April 2025 123 130 10.1109/ICCC64928.2025.10999126
  14. Kanthimathi M. Vijay P. Yeshwanth R.C. Akkash T.N. Sanjai P. Vishal A.S. Govindha R.E. Next-Generation Railway System for Inter-Train-to-Train Communication Using DSRC and LTE-R Based Intelligent Tunnels Proceedings of the 5th IEEE Global Conference for Advancement in Technology (GCAT) Bangalore, India 4–6 October 2024 1 7 10.1109/GCAT62922.2024.10924017
  15. Murthy K.K.K. Goel O. Jain S. Advancements in Digital Initiatives for Enhancing Passenger Experience in Railways Darpan Int. Res. Anal. 2023 11 40 60 10.36676/dira.v11.i1.71
  16. Mahesh N. Hadeed R. Marinov M. The Impact of Artificial Intelligence on Passenger Flow in Air and Rail Integrated Networks: A Systematic Literature Review Proceedings of the 20th European Dependable Computing Conference Companion Proceedings (EDCC-C) Lisbon, Portugal 8–11 April 2025 102 107 10.1109/EDCC-C66476.2025.00040
  17. Li H. Jiang Z. Li C. Gu J. Wang B. Formulation and Evaluation of Rail Transit Passenger Influx Control Schemes Based on Train-Passenger-Station Interactive Simulation Urban Rail Transit 2025 11 352 370 10.1007/s40864-025-00248-6
  18. Ojeda-Cabral M. Stead A.D. Estimating the impact of new rail station openings on through-passenger demand: A difference-in-differences approach Transportation 2025 1 28 10.1007/s11116-025-10684-9
  19. Luangboriboon N. Samà M. D’Ariano A. Fujiyama T. Train platforming problem from the viewpoint of passenger flow management Transportation 2025 1 23 10.1007/s11116-025-10650-5
  20. Fernández-Lobo A. Benavente J. Monzon A. Dynamic Management Tool for Improving Passenger Experience at Transport Interchanges Future Transp. 2025 5 59 10.3390/futuretransp5020059
  21. Bai J. Peng J. Wei Y. Xu S. Yan Z. Lu J. The Passenger Preferences for Flexible Tickets and Key Attributes for Ticket Design of High-speed Railway: A Case Study from China Urban Rail Transit 2025 11 321 334 10.1007/s40864-025-00249-5
  22. Khosla A. Dubey R. Cybersecurity Challenges in Modern Railway Signaling—A Comprehensive Review IJFMR 2025 7 1 20 10.36948/ijfmr.2025.v07i05.56254
  23. O’Kelly M.E. Transportation security at hubs: Addressing key challenges across modes of transport J. Transp. Secur. 2025 18 4 10.1007/s12198-025-00294-y
  24. Abudu R. Bridgelall R. Quayson B.P. Tolliver D. Dadson K. Railroad Cybersecurity: A Systematic Bibliometric Review Designs 2025 9 23 10.3390/designs9010023
  25. Kour R. Patwardhan A. Thaduri A. Kamir R. A review on cybersecurity in railways J. Rail Rapid Transit 2023 237 3 20 10.1177/09544097221089389
  26. Hsiao L.-S. Lin I.-L. Huang C.-J. Liu H.-T. Analysis of Factors Influencing Cybersecurity in Railway Critical Infrastructure: A Case Study of Taiwan Railway Corporation, Ltd Systems 2025 13 861 10.3390/systems13100861
  27. Soderi S. Masti D. Lun Y.Z. Railway Cyber-Security in the Era of Interconnected Systems: A Survey IEEE Trans. Intell. Transp. Syst. 2023 24 6764 6779 10.1109/TITS.2023.3254442
  28. Mazzino N. Perez X. Meuser U. Santoro R. Brennan M. Schlaht J. Chéron C. Samson H. Dauby L. Furio N. et al. Rail 2050 Vision. Rail—The Backbone of Europe’s Mobility 2018 Available online: https://errac.org/publications/rail-2050-vision-document/ (accessed on 27 December 2025)
  29. Zuo Z. Tian X. Shao Z. Deepening Research on the Comprehensive Application and Development of Railway Intelligent Detection and Monitoring System and Key Technologies Proceedings of the IEEE 7th Information Technology and Mechatronics Engineering Conference (ITOEC) Chongqing, China 15–17 September 2023 425 433 10.1109/ITOEC57671.2023.10291609
  30. Donato L. Tang R. Bešinović N. Flammini F. Goverde R. Lin Z. Liu R. Marrone S. Napoletano E. Nardone R. et al. Recommendations and Roadmaps Towards Intelligent Railways Transport Transitions: Advancing Sustainable and Inclusive Mobility McNally C. Carroll P. Martinez-Pastor B. Ghosh B. Efthymiou M. Valantasis-Kanellos N. Springer Cham, Switzerland 2026 10.1007/978-3-032-06763-0_25
  31. Chamaret A. Ernst J. Fernandez S. From Shift2Rail to Europe’s Rail, Future Perspectives for Alternative Drive Trains Standardizations and Energy Efficiency Transport Transitions: Advancing Sustainable and Inclusive Mobility McNally C. Carroll P. Martinez-Pastor B. Ghosh B. Efthymiou M. Valantasis-Kanellos N. Springer Cham, Switzerland 2025 169 175 10.1007/978-3-031-89444-2_50
  32. Narasimha S.S. Kushaal S. Kumar S. Aithal R. Vijayalakshmi M.N. Enhancing Railway Safety Through Human Activity Recognition Proceedings of the 8th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS) Bengaluru, India 7–9 November 2024 1 5 10.1109/CSITSS64042.2024.10816793
  33. International Union of Railways Future Railway Mobile Communication System. Functional Requirement Specification 2025 Available online: https://share.google/Ap3xOLAuMJhQZJWba (accessed on 27 December 2025)
  34. d’Arms A. Song H. Narman H.S. Yurtcu N.C. Zhu P. Alzarrad A. Automated Railway Crack Detection Using Machine Learning: Analysis of Deep Learning Approache Proceedings of the IEEE 15th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Berkeley, CA, USA 24–26 October 2024 1 7 10.1109/IEMCON62851.2024.11093324
  35. Menéndez M.N. Germino S. Díaz-Charris L.D. Lutenberg A. Automatic Railway Signaling Generation for Railways Systems Described on Railway Markup Language (railML) IEEE Trans. Intell. Transp. Syst. 2024 25 2331 2341 10.1109/TITS.2023.3317256
  36. Li X. He H. Yang Y. Fan Z. Automatic search model of railway shunting route based on improved artificial neural network algorithm Discov. Artif. Intell. 2025 5 231 10.1007/s44163-025-00484-6
  37. Hassan M. Al Nafees A. Shraban S.S. Paul A. Mahin D.H. Application of machine learning in intelligent transport systems: A comprehensive review and bibliometric analysis Discov. Civ. Eng. 2025 2 98 10.1007/s44290-025-00256-2
  38. Zhou M. Yuan Z. Wu X. Dong H. Wang F.-Y. A Railway Traffic Management Advisory System for High-Speed Trains in Case of Emergencies IEEE Intell. Transp. Syst. 2025 17 36 49 10.1109/MITS.2024.3512179
  39. Pascariu B. Flensburg J.V. Pellegrini P. Azevedo C.M.L. Formulation and solution framework for real-time railway traffic management with demand prediction IET Intell. Transp. Syst. 2025 19 e12610 10.1049/itr2.12610
  40. Alsobky A. Darwish A.M. Hassan A. A Multi-Objective Optimization Framework for Traffic Signal Design J. Southwest Jiatong Univ. 2023 58 474 492 10.35741/issn.0258-2724.58.1.37
  41. Lee Y.J. Human-Centered Intelligent Systems for Railroad Energy Management: A Behavioral Analysis Framework using Machine Learning for Technology Assessment and Social Impact Hum.-Centric Intell. Syst. 2025 5 351 375 10.1007/s44230-025-00107-4
  42. Liu W. Feng Q. Zeng X. Han Z. Deep Reinforcement Learning Based Automatic Speed Control Framework for Railway Trains with Rigid Contact Pantograph International Symposium for Intelligent Transportation and Smart City (ITASC) 2025 Proceedings Zeng X. Xie X. Sun J. Ma L. Chen Y. Springer Singapore 2025 Volume 1407 10.1007/978-981-96-4702-6_1
  43. Görçün Ö.F. Hussain A. Ullah K. Pamucar D. Simic V. Evaluation of Railway Intelligent Transportation Systems to Construct Safer Railway Transport Systems with a Novel Decision-Making Model Transp. Policy 2026 176 103897 10.1016/j.tranpol.2025.103897
  44. Noruzi M. Naderan A. Zakeri J.A. Rahimov K. A Novel Decision-Making Framework to Evaluate Rail Transport Development Projects Considering Sustainability under Uncertainty Sustainability 2023 15 13086 10.3390/su151713086
  45. Goodarzi S. Kashani H.F. Oke J. Ho C.L. Data-driven methods to predict track degradation: A. case study Constr. Build. Mater. 2022 344 128166 10.1016/j.conbuildmat.2022.128166
  46. Sauni M. Luomala H. Kolisoja P. Vaismaa K. Framework for implementing track deterioration analytics into railway asset management Built Environ. Proj. Asset Manag. 2022 12 871 886 10.1108/BEPAM-04-2022-0058
  47. Ghasemi A. Keshavarzi A. Abdelmoniem A.M. Nejati O.R. Derikvand T. Edge Intelligence for Intelligent Transport Systems: Approaches, challenges, and future directions Expert Syst. Appl. 2025 280 127273 10.1016/j.eswa.2025.127273
  48. Ye J. Wang C. Chen J. Wan R. Li X. Sepe A. Tai R. Cloud–Edge Hybrid Computing Architecture for Large-Scale Scientific Facilities Augmented with an Intelligent Scheduling System Appl. Sci. 2023 13 5387 10.3390/app13095387
  49. Liu X. Zhong Y. Bi C. Jiao F. Xu J. Research on the Application of Cloud Edge Collaboration Architecture in Power System J. Phys. Conf. Ser. 2024 2795 012022 10.1088/1742-6596/2795/1/012022
  50. Qin Y. Cao Z. Sun Y. Kou L. Zhao X. Wu Y. Liu Q. Wang M. Jia L. Research on Active Safety Methodologies for Intelligent Railway Systems Engineering 2023 27 266 279 10.1016/j.eng.2022.06.025
  51. Liu Y. Li P. Feng B. Pan P. Wang X. Zhao Q. Research on digital twin technology and its application in intelligent operation and maintenance of high-speed railway infrastructure Railw. Sci. 2024 3 746 763 10.1108/RS-09-2024-0036
  52. Thompson E.A. Lu P. Alimo P.K. Atuobi H.B. Akoto E.T. Abbew C.K. Revolutionizing railway systems: A systematic review of digital twin technologies HSR 2025 3 238 250 10.1016/j.hspr.2025.05.005
  53. Salierno G. Leonardi L. Cabri G. A Big Data Architecture for Digital Twin Creation of Railway Signals Based on Synthetic Data IEEE Intell. Transp. Syst. 2024 5 342 359 10.1109/OJITS.2024.3412820
  54. Ou Y. Mihăiţă A.-S. Ellison A. Mao T. Lee S. Chen F. Rail Digital Twin and Deep Learning for Passenger Flow Prediction Using Mobile Data Electronics 2025 14 2359 10.3390/electronics14122359
  55. Atanasov I. Vatakov V. Pencheva E. A Microservices-Based Approach to Designing an Intelligent Railway Control System Architecture Symmetry 2023 15 1566 10.3390/sym15081566
  56. Atanasov I. Pencheva E. Trifonov V. Kassev K. Railway Cloud: Management and Orchestration Functionality Designed as Microservices Appl. Sci. 2024 14 2368 10.3390/app14062368
  57. Atanasov I. Dimitrova D. Pencheva E. Trifonov V. Railway Cloud Resource Management as a Service Future Internet 2025 17 192 10.3390/fi17050192
  58. International Union of Railways Future Railway Mobile Communication System, User Requirements Specification 2020 Available online: https://uic.org/IMG/pdf/frmcs_user_requirements_specification_version_4.0.0.pdf (accessed on 27 December 2025)
  59. Kacar L. Use of Safety Guarantees of Train Protection in the Safety of Autonomous Train Driving J. Pol. Miner. Eng. Soc. 2025 2 1 6 10.29227/IM-2025-02-02-110
  60. Morin X. Olsson N.O.E. Lau A. Expected Challenges and Anticipated Benefits of Implementing Remote Train Control and Automatic Train Operation: A Tramway Case Study Future Transp. 2025 5 73 10.3390/futuretransp5020073
  61. Steffi Kumawat S. Gupta S. Flammini F. Conflict detection and resolution in IoT-Enabled railway systems using Petri nets JRTPM 2025 36 100553 10.1016/j.jrtpm.2025.100553
  62. Qiao Z. Tang T. Yuan L. Reordering and Driving Strategy to Resolve Train Conflict Based on Cooperative Game Theory Proceedings of the 23rd International Conference on Intelligent Transportation Systems (ITSC) Rhodes, Greece 20–23 September 2020 1 6 10.1109/ITSC45102.2020.9294290
  63. Matowicki M. Młyńczak J. Gołębiowski P. Přikryl J. Defining Railway Traffic Conflicts and Optimising Their Resolution: A Machine Learning Perspective Trans. Transp. Sci. 2025 16 44 48 10.5507/tots.2025.010
  64. Zawodny M. Kruszyna M. Szczepanek W.K. Korzeń M. A New Form of Train Detection as a Solution to Improve Level Crossing Closing Time Sensors 2023 23 6619 10.3390/s23146619 37514913
  65. Higgisson B. Byrne A. Davis E. Logan L. 2023 Annual Report to the European Union Agency for Railways, Commission for Railway Regulation Temple House, Blackrock, Co. Dublin, Ireland 2024 Available online: https://share.google/AVWCaX0jtQTuB4Yhr (accessed on 27 December 2025)
  66. Han W. Shi Z. Lv X. Zhang G. An Intelligent Heuristic Algorithm for a Multi-Objective Optimization Model of Urban Rail Transit Operation Plans Sustainability 2025 17 4617 10.3390/su17104617
  67. Wang Y. Song R. He S. Song Z. Chi J. Optimizing Train Routing Problem in a Multistation High-Speed Railway Hub by a Lagrangian Relaxation Approach IEEE Access 2022 10 61992 62010 10.1109/ACCESS.2022.3181815
  68. Zhou X. Lu F. Wang L. Optimization of Train Operation Planning with Full-Length and Short-Turn Routes of Virtual Coupling Trains Appl. Sci. 2022 12 7935 10.3390/app12157935
  69. Ma Y. Optimization Algorithm of Urban Rail Transit Network Route Planning Using Deep Learning Technology Comput. Intell. Neurosci. 2022 2022 2024686 10.1155/2022/2024686 35875736
  70. Bao Z. Zhang T. Liu J. Shen D. Cai B. Composite Iterative Learning and Model Reference Adaptive Control for High-Speed Train Speed Tracking Proceedings of the IEEE 14th Data Driven Control and Learning Systems (DDCLS) Wuxi, China 9–11 May 2025 1834 1839 10.1109/DDCLS66240.2025.11065695
  71. Guo Y. Ding J. Feng X. Sun P. Fang Q. Wei M. Robust adaptive iterative learning control for high-speed trains under non-strictly repeated conditions Control Eng. Pract. 2024 145 105865 10.1016/j.conengprac.2024.105865
  72. Garrisi G. Cervelló-Pastor C. Train-Scheduling Optimization Model for Railway Networks with Multiplatform Stations Sustainability 2020 12 257 10.3390/su12010257
  73. Wang S. Chow A.H.F. Ying C.-S. Adaptive and flexible rail transit network service dispatching as a partially observable Markov decision process Transp. Res. Part C Emerg. Technol. 2025 179 105286 10.1016/j.trc.2025.105286
  74. Guo Y. Sun P. Wang Q. Feng X. Adaptive cooperative control for multiple high-speed trains with uncertainties, input saturations and state constraints Control Eng. Pract. 2024 142 105768 10.1016/j.conengprac.2023.105768
  75. Yang X. Meng J. Adaptive distributed cooperative tracking control of high-speed trains based on consensus algorithm Proceedings of the International Conference on Electrical Engineering and Intelligent Systems (IC2EIS 2025) Chengdu, China 31 July 2025 10.1117/12.3069067
  76. Yang C. Sun Y. Ladubec C. Liu Y. Developing Machine Learning-Based Models for Railway Inspection Appl. Sci. 2021 11 13 10.3390/app11010013
  77. European Union, Agency for Railways Report on Railway Safety and Interoperability in the EU 2024 Available online: https://share.google/hwPj8kULZ0BxlOTKY (accessed on 27 December 2025)
  78. Solinen E. Palmqvist C.-W. Development of new railway timetabling rules for increased robustness Transp. Policy 2023 133 198 208 10.1016/j.tranpol.2023.02.003
  79. Lövétei I.F. Lindenmaier L. Aradi S. Efficient real-time rail traffic optimization: Decomposition of rerouting, reordering, and rescheduling problems JRTPM 2025 33 100496 10.1016/j.jrtpm.2024.100496
  80. Morin X. Olsson N.O.E. Lau A. Managerial Challenges in Implementing European Rail Traffic Management System, Remote Train Control, and Automatic Train Operation: A Literature Review Future Transp. 2024 4 1350 1369 10.3390/futuretransp4040065
  81. International Union of Railways Future Railway Mobile Communication System, Use Cases 2020 Available online: https://uic.org/IMG/pdf/frmcs_use_cases-mg_7900-v2.1_0.pdf (accessed on 27 December 2025)
  82. Sarmiento C. Bourgne G. Ganascia J.-G. Formalising Overdetermination in a Labelled Transition System Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems Detroit, MI, USA 19–23 May 2025 1840 1848
  83. European Telecommunications Standard Institute Technical Report: Rail Telecommunications (RT); Future Rail Mobile Communication System (FRMCS); Study on System Architecture Available online: https://share.google/K5N0Oj5LKxt9b3hgX (accessed on 27 December 2025)

Issue

Future Transportation, vol. 6, 2026, Switzerland, https://doi.org/10.3390/futuretransp6010018

Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science