MODEL OF MANAGEMENT, IMPLEMENTATION AND PLANNING OF BUSINESS PROCESSES IN A RAILWAY COMPANY BASED ON ARTIFICIAL INTELLIGENCE

Zoran G. Pavlović; Ana Savić

Scientific paper ID 2728 : 2025/3

MODEL OF MANAGEMENT, IMPLEMENTATION AND PLANNING OF BUSINESS PROCESSES IN A RAILWAY COMPANY BASED ON ARTIFICIAL INTELLIGENCE

Zoran G. Pavlović, Ana Savić

Realization of regular business processes in large and complex economic sectors s safety, security and functionality that are in accordance with the mission and vision that was foreseen in advance. The above basic criteria directly and indirectly affect the quality of the service or product. A large number of business tasks are performed by employees directly or indirectly, where an unplanned action can occur that negatively affects the functioning of the entire system. The solution for such situations can be the implementation and application of advanced Internet technologies. This paper presents the basis for improving the mentioned criteria in the railway company in traffic and transport, where at the same time the existing computer system is modernized. The role of the employee is reduced or abolished in order to reduce the consequences of fatigue, lack of knowledge or incompetence. Applying artificial intelligence (AI) technologies to the existing infrastructure computing system can address the gap that needs to be addressed. AI is increasingly represented in the transformation of digital processes, where agents are created for the management, organization, and implementation and planning of autonomous computer systems in intelligent transport systems (ITS). It covers the basic concepts of AI and presents the advantages and disadvantages (anomalies) specifically on the example of application in railway traffic and transport. The paper presents a theoretical and practical framework that can be implemented in the railway company in order to increase all segments of quality in the near future.

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advanced internet technologies artificial intelligence intelligent agents rail traffic and transport service or product qualityadvanced internet technologies artificial intelligence intelligent agents rail traffic and transport service or productZoran G. Pavlović Ana Savić

BIBLIOGRAPHY

[1] Z. G. PAVLOVIĆ, ”Development Of Models Of Smart Intersections In Urban Areas Based On IoT Technologies,” 2022 21st International Symposium Infoteh-Jahorina (Infoteh), 2022, pp. 1-4, doi: 10.1109/INFOTEH53737.2022.9751263.

[2] VANIO RALEV, DOBRINKA ATMADZHOVA, Failure Analysis In Passenger Bogies From The Railway System Of The Republic Of Bulgaria, IMK-14 – Research&Developement 27 (2021)3, EN89-98, UDC 621 ISSN 0354-6829, doi: 10.5937/IMK2103089R, 2021.

[3] ATMADZHOVA D., RALEV V., Strength Analysis Of Passenger Bogie Elements Operated In Bulgarian State Railways, I International Symposium Rail Transport In The Modern World, Higher Education Railway School of Professional Studies Belgrade, Serbia, 12-13.12.2019, ISBN 978-86-81101-32-2, р. 1-6, 2019,

[4] STOYANOVA P., Improvement Of Spare Parts Stock Management System For Locomotive Depot, International Xxi Scientific - Expert Conference On Railways Railcon ‘24, October 10 - 11, 2024, Niš, Serbia, pp. 125-129, DOI: 10.5937/Railcon24127S

[5] BEROV T., BORISOV A., STOYANOVA P., Analysis of the environmental impact caused by urban freight transport and logistics” Sofia VTU, 6-7.07.22, Scientific Journal ”Mechanics Transport Communications”, vol.20, issue 3, 2022, ISSN 2367-6620 (online). https://mtc-aj.com/library/2295.pdf

[6] N. BEŠINOVIĆ et al., ”Artificial Intelligence in Railway Transport: Taxonomy, Regulations, and Applications,” in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 9, pp. 14011-14024, Sept. 2022, doi: 10.1109/TITS.2021.3131637

[7] W. XU et al., ”Parallel Testing for Centralized Traffic Control Systems of Intelligent Railways,” in IEEE Transactions on Intelligent Vehicles, vol. 8, no. 9, pp. 4249-4262, Sept. 2023, doi: 10.1109/TIV.2023.3305543.

[8] P. SIKORA et al., ”Artificial Intelligence-Based Surveillance System for Railway Crossing Traffic,” in IEEE Sensors Journal, vol. 21, no. 14, pp. 15515-15526, 15 July15, 2021, doi: 10.1109/JSEN.2020.3031861

[9] S. GHABOURA, R. FERDOUSI, F. LAAMARTI, C. YANG AND A. E. SADDIK, ”Digital Twin for Railway: A Comprehensive Survey,” in IEEE Access, vol. 11, pp. 120237-120257, 2023, doi: 10.1109/ACCESS.2023.3327042.

[10] H. ALAWAD, S. KAEWUNRUEN AND M. AN, ”Learning From Accidents: Machine Learning for Safety at Railway Stations,” in IEEE Access, vol. 8, pp. 633-648, 2020, doi: 10.1109/ACCESS.2019.2962072.

[11] W. XU et al., ”Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling,” in IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 9, pp. 1822-1833, September 2023, doi: 10.1109/JAS.2023.123501.

[12] J. SRESAKOOLCHAI AND S. KAEWUNRUEN, ”Integration of Building Information Modeling and Machine Learning for Railway Defect Localization,” in IEEE Access, vol. 9, pp. 166039-166047, 2021, doi: 10.1109/ACCESS.2021.3135451.

[13] J. SHENG et al., ”Space-Air-Ground Integrated Network Development and Applications in High-Speed Railways: A Survey,” in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, pp. 10066-10085, Aug. 2022, doi: 10.1109/TITS.2021.3118557.

[14] SINGHAL V., et al., ”Artificial Intelligence Enabled Road Vehicle-Train Collision Risk Assessment Framework for Unmanned Railway Level Crossings,” in IEEE Access, vol. 8, pp. 113790-113806, 2020, doi: 10.1109/ACCESS.2020.3002416.