Forthcoming

Improvement of data flow management in the air traffic control automation system

Authors

Keywords:

data flow management, air traffic control system, information load

Abstract

Purpose. The research purpose is to improve the data flow management of the air traffic control system of the Danylo Halytskyi International Airport “Lviv”. Design / Method / Approach. The following methods and approaches were consistently used in the research: system approach; modeling; content analysis; statistical analysis; project approach; economic analysis. Findings. Recommendations have been developed for optimizing data flow processing, including improving technological solutions, increasing the level of automation, and implementing strategies to reduce stress on controllers. The features and effectiveness of air traffic management and the data flow network of the automated control system of the Danylo Halytskyi International Airport “Lviv” have been studied. The program has been developed to improve the effectiveness of air traffic management and the data flow network of the automated control system of the Danylo Halytskyi International Airport “Lviv”. The effectiveness of the implementation of the program to improve air traffic management and the data flow network of the automated control system of the Danylo Halytskyi International Airport “Lviv” has been substantiated. Theoretical Implications. Methodological aspects of data flow management of the automated air traffic control system network have been investigated. Practical Implications. Directions for increasing the efficiency of air traffic control and data flow management of the automated control system network of the Danylo Halytskyi International Airport “Lviv” have been developed and substantiated. Originality / Value. The implementation of the modern technical and methodological solutions proposed in the article for the automation of air traffic control and data processing will contribute to reducing risks, increasing the speed of decision-making and ensuring the stable operation of all aviation processes. Research Limitations / Future Research. Future research into mechanisms for improving air traffic management and data flows at airports is an important task from both a scientific and a practical point of view. Article Type. Applied Research.

PURL: https://purl.org/cims/4.281

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References

Abdulhak, S., Carvette, A., Shen, K., Goldman, R., Tuck, B., & Li, M. Z. (2024). User Feedback-Informed Interface Design for Flow Management Data and Services (FMDS). arXiv preprint arXiv:2402.12635. https://doi.org/10.48550/arXiv.2402.12635

Aditya, V., Aswin, D. S., Dhaneesh, S. V., Chakravarthy, S., Kumar, B. S., & Venkadavarahan, M. (2024). A review on air traffic flow management optimization: trends, challenges, and future directions. Discover Sustainability, 5(1). https://doi.org/10.1007/s43621-024-00781-7

Bao, J., Kang, J., Zhang, J., Zhang, Z., & Han, J. (2025). A dynamic control method for airport ground movement optimization considering adaptive traffic situation and data-driven conflict priority. Journal of Air Transport Management, 124, 102753. https://doi.org/10.1016/j.jairtraman.2025.102753

Brusakova, O. V. (2019). State Regulation of the Use of Ukrainian Airspace [In Ukrainian]. Scientific Journal of Public and Private Law, 6, 142–148. https://doi.org/10.32844/2618-1258.2019.6.24

Chen, Y., Zhao, Y., & Wu, Y. (2024). Recent progress in air traffic flow management: A review. Journal of Air Transport Management, 116, 102573. https://doi.org/10.1016/j.jairtraman.2024.102573

Hu, H., Sun, J., & Du, B. (2025). Air Traffic Management in Dense Airspace via Network Flow Optimization. Journal of Aerospace Information Systems, 1–14. https://doi.org/10.2514/1.i011474

Jameel, M., Tyburzy, L., Gerdes, I., Pick, A., Hunger, R., & Christoffels, L. (2023). Enabling Digital Air Traffic Controller Assistant through Human-Autonomy Teaming Design. 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), 1–9. https://doi.org/10.1109/dasc58513.2023.10311220

Kalashnyk, G., & Kalashnyk-Rybalko, M. (2024a). Architectural Features of a Promising Intelligent Space Weather Data Processing System for Increasing the Efficiency of Radio Equipment of Civil Aviation for the Conditions of Ukraine. In International Conference of Young Professionals “GeoTerrace-2024” (pp. 1–5). Cham: European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.2024510090

Kalashnyk, G., & Kalashnyk-Rybalko, M. (2024b). Methodology for ensuring the functional stability of aircraft integrated modular avionics complex. Science and technology of the Ukrainian Air Force, 4(53), 30–40. https://doi.org/10.30748/nitps.2023.53.04

Kang, J., Bao, J., Zhang, Z., Zhang, J., & Wang, W. (2025). Dynamic Routing and Scheduling Approach for Aircraft Taxi Automation with Adaptive Surface Situation. Journal of Aerospace Information Systems, 22(3), 189–201. https://doi.org/10.2514/1.i011486

LLC Clarity App. (2021). Financial Reporting of State Enterprise "Lviv Danylo Halytskyi International Airport" for 2021, Legal ID 33073442 [In Ukrainian]. Clarity Project. https://clarity-project.info/edr/33073442/yearly-finances?current_year=2021

LLC Clarity App. (2022). Financial Reporting of State Enterprise "Lviv Danylo Halytskyi International Airport" for 2022, Legal ID 33073442 [In Ukrainian]. Clarity Project. https://clarity-project.info/edr/33073442/yearly-finances?current_year=2022

LLC Clarity App. (2023). Financial Reporting of State Enterprise "Lviv Danylo Halytskyi International Airport" for 2023, Legal ID 33073442 [In Ukrainian]. Clarity Project. https://clarity-project.info/edr/33073442/yearly-finances?current_year=2023

Mashkov, O., Bychkov, A., Kalahnik, G., Shevchenko, V., & Vyshemyrska, S. (2022). Application of the Theory of Functional Stability in the Problems of Covering Territories by Sensory Networks. In International Scientific Conference “Intellectual Systems of Decision Making and Problem of Computational Intelligence” (pp. 266-285). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-16203-9_16

Ministry of Transport of Ukraine. (2010). On Approval of the Instruction on the Organization and Implementation of Objective Control in Air Traffic Services and Production Activities of Civil Aviation of Ukraine, Order No. 872 [In Ukrainian]. Verkhovna Rada of Ukraine. https://zakon.rada.gov.ua/laws/show/z1103-03

Permiakov, O., Korolyuk, N., Golubnychiy, D., & Skoropaniuk, P. (2021). Algorithm of multifractal loading balance of special purpose information telecommunications networks [In Ukrainian]. Modern Information Technologies in the Sphere of Security and Defense, 42(3), 63–70. https://doi.org/10.33099/2311-7249/2021-42-3-63-70

Pinto Neto, E. C., Baum, D. M., Almeida, J. R. de, Camargo, J. B., & Cugnasca, P. S. (2023). Deep Learning in Air Traffic Management (ATM): A Survey on Applications, Opportunities, and Open Challenges. Aerospace, 10(4), 358. https://doi.org/10.3390/aerospace10040358

Ukrainian State Air Traffic Services Enterprise. (2025). Official website of Ukrainian State Air Traffic Services Enterprise (UkSATSE). http://uksatse.ua

Vaidya, P., & Kamdar, V. (2025). A Modern Approach to Real-Time Air Traffic Management System. arXiv preprint arXiv:2504.03652. https://doi.org/10.48550/arXiv.2504.03652

Wang, H., Huang, J., Deng, T., & Song, Z. (2023). Evaluation and Optimization of Air Traffic Complexity Based on Resilience Metrics. Journal of Advanced Transportation, 2023, 1–16. https://doi.org/10.1155/2023/5692934

Xie, Y., Pongsakornsathien, N., Gardi, A., & Sabatini, R. (2021). Explanation of Machine-Learning Solutions in Air-Traffic Management. Aerospace, 8(8), 224. https://doi.org/10.3390/aerospace8080224

Yousefzadeh Aghdam, M., Kamel Tabbakh, S. R., Mahdavi Chabok, S. J., & Kheyrabadi, M. (2021). Optimization of air traffic management efficiency based on deep learning enriched by the long short-term memory (LSTM) and extreme learning machine (ELM). Journal of Big Data, 8(1). https://doi.org/10.1186/s40537-021-00438-6

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Published

2025-05-11

How to Cite

Kalashnyk, G., Kalashnyk-Rybalko, M., & Mykhailetskyi, A. (2025). Improvement of data flow management in the air traffic control automation system. Challenges and Issues of Modern Science. https://cims.fti.dp.ua/j/article/view/281

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