An emulation oriented method and tool for test of ground traffic control systems at airports

    Farid Saifutdinov   Affiliation
    ; Ilya Jackson Affiliation
    ; Jurijs Tolujevs Affiliation


The paper discusses the prospects for the development and implementation of centralized ground traffic control systems at airports. The automatic control system can only work if there is accurate data on the location of mobile objects, which include both vehicles involved in the maintenance of aircraft and the aircraft themselves. In order to develop and test software for any specific centralized control system, the emulation mode should be used, in which the simulation model of the airport transport network works in conjunction with the real control software. In this case, one of the main functions of the simulation model is the generation of data streams that appropriately reflect the processes of movement of objects in the transport network of a specific airport. The paper describes a universal simulation program that allows one to simulate precisely described scenarios for the process in a transport network, which necessitates decision-making at the level of a centralized control system. The movement of objects in the model is accompanied by the recording of their coordinates in the Digital Twin. In this way, real streams of measurement data from various systems for determining the position of moving objects are modeled and stored.

Keyword : airport, ground traffic, centralized control, simulation, emulation, data flows, digital twin

How to Cite
Saifutdinov, F., Jackson, I., & Tolujevs, J. (2022). An emulation oriented method and tool for test of ground traffic control systems at airports. Aviation, 26(2), 104–111.
Published in Issue
Jun 10, 2022
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Airport Research Center. (n.d.). Cast vehicle ground handling. Retrieved June 9, 2021, from

ArcPORT. (n.d.). Comprehensive and powerful terminal simulation. Retrieved June 9, 2021, from

Astarita, V., Giofre, V. P., Festa, D. C., Guido, G., & Vitale, A. (2020). Floating car data adaptive traffic signals: A description of the first real-time experiment with “connected” vehicles. Electronics, 9(1), 1014.

Astarita, V., Guido, G., Vitale, A., & Giofré, V. (2012). A new microsimulation model for the evaluation of traffic safety performances. European Transport, 51(1), 1–16.

Atac. (n.d.). Simmod PRO! Advanced simulation tool for analyses. Retrieved June 9, 2021, from

Augustyn, S., & Znojek, B. (2015, 28–30 May). The new vision in design of airport. In International Conference of Scientific Paper AFASES (Vol. 2, pp. 369–372). Brasov.

Bertino, J., Boyajian, E., & Johnson, N. (2011). 21st century, fast-time airport and airspace modeling analysis with Simmod. Managing the Skies, 9(3), 21–23.

Chen, Y., Shafi, S. Y., & Chen, Y. (16 May, 2020). Simulation pipeline for traffic evacuation in urban areas and emergency traffic management policy improvements. arXiv:2002.06198v2 [cs.AI].

Dimitropoulos, K., Grammalidis, N., Simitopoulos, D., Pavlidou, N., & Strintzis M. (2005). Aircraft detection and tracking using intelligent cameras. In IEEE International Conference on Image Processing (pp. 594–597). Genova.

EUROCONTROL. (2020). Specification for Advanced-Surface Movement Guidance and Control System (A-SMGCS) Services (Ed. 2.0, published 22 April 2020).

Helleboogh, A., Holvoet, T., & Berbers, Y. (2006). Testing AGVs in dynamic warehouse environments. In D. Weyns, H. Van Dyke Parunak, & F. Michel (Eds.), Environments for Multi-Agent Systems II. E4MAS 2005. Lecture Notes in Computer Science, 3830, 270–290. Springer.

International Air Transport Association. (2011, February 12). Vision 2050. Singapore.

Jeppesen. (n.d.). Jeppesen total airspace and airport modeler. Retrieved June 9, 2021, from

Kaidi, Z. (2019). Design and implementation of a centralized monitoring system for a remote control tower system. In the IEEE 1st International Conference on Civil Aviation Safety and Information Technology (ICCASIT) (pp. 498–503). IEEE.

Law, A. M., & Kelton, W. D. (2000). Simulation modeling and analysis (3rd ed.). McGraw-Hill.

Lee, S., Lee, D., Choi, P., & Park, D. (2020). Accuracy-Power Controllable LiDAR sensor system with 3D object recognition for autonomous vehicle. Sensors, 20(19), 5706.

Lopez, P., A., Behrisch, M., Bieker-Walz, L. Erdmann, J., Flötteröd, Y.-P., Hilbrich, R., Lücken, L., Rummel, J., Wagner, P., & Wiessner, E. (2018). Microscopic traffic simulation using SUMO. In The 21st IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 2575–2582). Maui, Hi, USA. IEEE.

Rintanen, K., & Thomas, A. (2021). Container terminal automation. A PEMA information paper. Retrieved June 9, 2021, from

Saifutdinov, F., & Tolujevs, J. (2020a). Analysis of navigation systems for landside transport processes control. In Reliability and Statistics in Transportation and Communication. Lecture Notes in Network and Systems, 117, 552–561. Springer.

Saifutdinov, F., & Tolujevs, J. (2020b). A model for ground transportation systems simulation at airports under centralized control. Communications of the ECMS, 34(1), 5–10.

Saifutdinov, F., & Tolujevs, J. (2021). Time and space discretization in the digital twin of the airport transport network. Transport and Telecommunication Journal, 22(3), 257–265.

Saifutdinov, F., Jackson, I., Tolujevs, J., & Zmanovska, T. (2020). Digital twin as a decision support tool for airport traffic control. In the 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2020) (pp. 1–5). Riga, Latvia. IEEE.

Spieckermann, S., Stauber, S., & Bleifuß, R. (2012). A case study on simulation and emulation of a new case picking system for a US based wholesaler. In Proceedings of the 2012 Winter Simulation Conference (pp. 1490–1501). IEEE.

Xcelgo. (2020). Emulation vs simulation – what is the difference?