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Air traffic controller keyboard optimization by artificial evolution

Abstract : The annual number of daily flights in France has increased from about 3500 in 1982 to about in 8000 in 2000. The number of flights simultaneously present on the radar screen of the controller has also increased. Usually controllers manage about 15 aircraft on their position and sometime this number reach a maximum of 20. On the radar screen, aircraft are represented by spots (with some previous positions and their speed vector) and the associated label which give the flight ID, the speed and the altitude of the aircraft. The controller in charge of the controlled area, has to be able to select any aircraft in order to manipulate some parameters of the flight such as heading, speed, altitude etc. Aircraft selection is done by the mean of a virtual keyboard where the controller pressed the keys of the flight ID. This ID is composed by a sequence of three letters (maximum) which represents the airline code, followed by the flight number. When such a selection is done, the associated flight is made highlighting on the radar screen. Depending of the flight ID distribution on a control position, the virtual keyboard can be optimized in order to speed up the aircraft selections and to improve the work of the controllers mainly when the sectors are overloaded. This keyboard optimization problem may be addressed like a pure assignment problem which is NP_Hard. This paper shows how artificial evolution has been used for solving such a problem with very good results on real instance associated to the Roissy departure sector.
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Soumis le : jeudi 3 juillet 2014 - 17:29:01
Dernière modification le : mardi 19 octobre 2021 - 11:02:49
Archivage à long terme le : : vendredi 3 octobre 2014 - 10:40:30


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Daniel Delahaye, Stéphane Puechmorel. Air traffic controller keyboard optimization by artificial evolution. Lecture Notes in Computer Science, 2003, Lecture Notes in Computer Science, 2936, pp 177-188. ⟨10.1007/978-3-540-24621-3_15⟩. ⟨hal-01004101⟩



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