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Classification of air traffic control scenarios using decision trees: insights from a field study in terminal approach radar environment

Malakis, Stathis, Psaros Panagiotis, Kontogiannis Thomas, Malaki Christina

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URIhttp://purl.tuc.gr/dl/dias/0ED4464C-04E2-4470-8086-02C0708A4F58-
Identifierhttps://doi.org/10.1007/s10111-019-00562-7-
Identifierhttps://link.springer.com/article/10.1007%2Fs10111-019-00562-7-
Languageen-
Extent21 pagesen
TitleClassification of air traffic control scenarios using decision trees: insights from a field study in terminal approach radar environmenten
CreatorMalakis, Stathisen
CreatorPsaros Panagiotisen
CreatorKontogiannis Thomasen
CreatorΚοντογιαννης Θωμαςel
CreatorMalaki Christinaen
PublisherSpringer Natureen
Content SummaryAir traffic controllers are responsible for the safe, expeditious and orderly flow of the air traffic. Their training relies heavily on the use of simulators that can represent various normal and emergency situations. Accurate classification of air traffic scenarios can provide assistance towards a better understanding of how controllers respond to the complexity of a traffic scenario. To this end, we conducted a field study using qualified air traffic controllers, who participated in simulator sessions of terminal radar approach control in a variety of scenarios. The aim of the study was twofold, firstly to explore how decision trees and classification rules can be used for realistic classification of air traffic scenarios and secondly to explore which factors reflect better operational complexity. We applied machine learning methods to the data and developed decision trees and classification rules for these scenarios. Results indicated that decision trees and classification rules are useful tools in accurately categorizing scenarios and that complexity requires a larger set of predictors beyond simple aircraft counts. The derived decision trees and classification rules performed well in prediction, stability and interpretability. Practical benefits can be derived in the areas of operations and system design in the context of air traffic flow and capacity management systems.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2021-09-21-
Date of Publication2020-
SubjectAir traffic controlen
SubjectAir traffic flow managementen
SubjectMachine learningen
SubjectDecision treesen
SubjectClassification rulesen
SubjectComplexityen
Bibliographic CitationS. Malakis, P. Psaros, T. Kontogiannis, and C. Malaki, “Classification of air traffic control scenarios using decision trees: insights from a field study in terminal approach radar environment,” Cogn. Technol. Work, vol. 22, no. 1, pp. 159–179, Feb. 2020. doi: 10.1007/s10111-019-00562-7en

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