Abstract
Aircraft enroute flights are supervised by area air traffic controllers supported by telematics systems, ensuring communication and visualization. Based on them, controllers make decisions regarding the aircraft movement. The air traffic controller workload is the basic factor determining the safety of flight operations. The aim of this research was to develop a simulation method for assessing the controller time workload. The method presented in the paper uses a mathematical model that simultaneously considers the air traffic and the work of the controller. The model created as a colored timed Petri net, allows for estimating the controller time workload for various parameters of the traffic flow, infrastructure and support systems. As part of simulation experiments, the quantitative dependence of time workload on the traffic volume was demonstrated. It has been shown that, for the modeled sector, maintaining the traffic in accordance with a predetermined flight plans reduces the controller’s workload, and granting clearances for direct flights, although beneficial for flight economics, increases workload and, therefore, may affect traffic safety.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bekier, M., Molesworth, B., Williamson, A.: Tipping point: the narrow path between automation acceptance and rejection in air traffic management. Saf. Sci. 50(2), 259–265 (2012)
Brooker, P.: Air traffic management safety challenges. In: 2nd Institution of Engineering and Technology System Safety Conference, pp. 1–45 (2007)
Corver, S., Unger, D., Grote, G.: Predicting air traffic controller workload: trajectory uncertainty as the moderator of the indirect effect of traffic density on controller workload through traffic conflict. Hum. Factors 58(4), 560–573 (2016)
Dmochowski, P.A., Skorupski, J.: Air traffic smoothness as a universal measure for air traffic quality assessment. Procedia Eng. 134, 237–244 (2016)
Dmochowski, P.A., Skorupski, J.: Air traffic smoothness. A new look at the air traffic flow management. Transp. Res. Procedia 28, 127–132 (2017)
EUROCONTROL. Description of the CAPAN method, Bruxells. https://www.eurocontrol.int/sites/default/files/field_tabs/content/documents/nm/airspace/airspace-capan.pdf. Accessed 10 Dec 2018
Ferduła, P., Skorupski, J.: The influence of errors in visualization systems on the level of safety threat in air traffic. J. Adv. Transp. 2018, 1–16 (2018). Article ID 1034301
Inoue, S., et al.: Cognitive process modelling of controllers in en route air traffic control. Ergonomics 55(4), 450–464 (2012)
Jensen, K., Kristensen, L., Wells, L.: Coloured Petri nets and CPN tools for modelling and validation of concurrent systems. Int. J. Softw. Tools Technol. Transf. 9(3–4), 213–254 (2007)
Langan-Fox, J., et al.: Human factors measurement for future air traffic control systems. Hum. Factors 51(5), 595–637 (2010)
Lehouillier, T., et al.: Measuring the interactions between air traffic control and flow management using a simulation-based framework. Comput. Ind. Eng. 99, 269–279 (2016)
Malarski, M., Walczak, K.: A contemporary approach to air traffic management systems on the example of the PEGASUS_21 system being implemented, vol. 89, pp. 109–134. Scientific Works of Warsaw University of Technology, Transport (2013). (in Polish)
Nealley, M., Gawron, V.: The effect of fatigue on air traffic controllers. Int. J. Aviat. Psychol. 25(1), 14–47 (2015)
Ratzer, A.V., et al.: CPN tools for editing, simulating, and analysing coloured Petri nets. In: van der Aalst, W.M.P., Best, E. (eds.) ICATPN 2003. LNCS, vol. 2679, pp. 450–462. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-44919-1_28
Rohacs, J., Rohacs, D., Jankovics, I.: Conceptual development of an advanced air traffic controller workstation based on objective workload monitoring and augmented reality. J. Aerosp. Eng. 230(9), 1747–1761 (2016)
Sáez Nieto, F., et al.: Development of a three-dimensional collision risk model tool to assess safety in high density en-route airspaces. J. Aerosp. Eng. 224, 1119–1129 (2010)
Skorupski, J.: ATC sector capacity as a measure of air traffic safety. In: Safety, Reliability and Risk Analysis: Beyond the Horizon - Proceedings of the European Safety and Reliability Conference, ESREL 2013, pp. 1827–1835. Taylor & Francis, London (2014)
Számel, B., Szabó, G.: Supporting safety management systems of air traffic controllers by analyzing human-technical interactions. In: 25th European Safety and Reliability Conference, ESREL 2015, pp. 3119–3128 (2015)
Tobaruela, G.: Capacity estimation for the single european sky. In: 5th International Conference on Research and Air Transportation, Berkeley, USA, pp. 1–8 (2012)
Westin, C., Borst, C., Hilburn, B.: Automation transparency and personalized decision support: air traffic controller interaction with a resolution advisory system. IFAC-PapersOnLine 49(19), 201–206 (2016)
Zhang, M., et al.: Terminal airspace sector capacity estimation method based on the ATC dynamical model. Kybernetes 45(6), 884–899 (2016)
Zohrevandi, E., et al.: Modeling and analysis of controller’s taskload in different predictability conditions. In: 6th SESAR Innovation Days, Delft, the Netherlands, pp. 1–8 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Dmochowski, P.A., Skorupski, J. (2019). A Method of Evaluating Air Traffic Controller Time Workload. In: Mikulski, J. (eds) Development of Transport by Telematics. TST 2019. Communications in Computer and Information Science, vol 1049. Springer, Cham. https://doi.org/10.1007/978-3-030-27547-1_26
Download citation
DOI: https://doi.org/10.1007/978-3-030-27547-1_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27546-4
Online ISBN: 978-3-030-27547-1
eBook Packages: Computer ScienceComputer Science (R0)