Functional model of a decision support tool for Air Traffic Control supervisors

Számel, Bence, Szabó, Géza (2018) Functional model of a decision support tool for Air Traffic Control supervisors Annales Mathematicae et Informaticae. 48. pp. 65-73. ISSN 1787-5021 (Print), 1787-6117 (Online)

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The optimization of operator workload in Air Traffic Control systems is of high importance regarding both safety and efficiency of air transportation. The default means of optimizing workload in practice is division of traffic among controllers by splitting the airspace into sectors. Decisions about opening or closing sectors are made by a human supervisor who can sometimes encounter difficulties during decision making, especially when facing uncommon traffic situations. This makes it advisable to create a decision support tool designed to automate decision making by suggesting a sector configuration based on traffic complexity to the supervisor. The main modules of this tool are centered on a model of cognitive functions that have to be executed by the supervisor throughout the decision making process. The functions include prediction of future traffic, calculation of complexity and determining optimal sector states to finally produce the optimal configuration. In this paper, we outline the formal description of the functionality of the tool’s modules, focusing on the algorithms they should implement.

Mű típusa: Folyóiratcikk
Szerző:
Szerző neveMTMT azonosítóORCID azonosítóKözreműködés
Számel, BenceNEM RÉSZLETEZETTNEM RÉSZLETEZETTSzerző
Szabó, GézaNEM RÉSZLETEZETTNEM RÉSZLETEZETTSzerző
Megjegyzés: Selected papers of the 10th International Conference on Applied Informatics
Kapcsolódó URL-ek:
Kulcsszavak: Air Traffic Control, decision support, neural network
Nyelv: angol
Kötetszám: 48.
ISSN: 1787-5021 (Print), 1787-6117 (Online)
Felhasználó: Tibor Gál
Dátum: 13 Már 2019 18:54
Utolsó módosítás: 13 Már 2019 18:54
URI: http://publikacio.uni-eszterhazy.hu/id/eprint/3314
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