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GeoInformatica
Erschienen in: GeoInformatica 3/2023

30.08.2022

Geographical information system for air traffic optimization using genetic algorithm

verfasst von: Rafik Amara, Mostefa Belhadj Aissa, Rebiha Kemcha, Maamar Bougherara, Nadjib Louam

Erschienen in: GeoInformatica | Ausgabe 3/2023

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Abstract

The primary concern of an air traffic controller is to ensure the safety and fluidity of ever-increasing air traffic. This requires effective training through practical work supervised by instructors. Based on certain rules called separation rules, the trainee must find a solution to a traffic configuration defined by flight plans (FPL) initially containing a number of conflicts. This solution will then be compared to the one proposed by the instructor. The purpose of this article is to replace the instructor with a Geographical Information System (GIS) solution combined with a genetic algorithm which, from a set of FPLs, will find the best solution to ensure on the one hand the safety of the aircraft but also minimizing the distance and the changes to be made. The application will use the GAMA platform, very suitable for this and a set of tests composed of actual exercises will be performed to validate the work.
Vorheriger Artikel Optimizing vessel trajectory compression for maritime situational awareness
Nächster Artikel GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

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Metadaten
Titel
Geographical information system for air traffic optimization using genetic algorithm
verfasst von
Rafik Amara
Mostefa Belhadj Aissa
Rebiha Kemcha
Maamar Bougherara
Nadjib Louam
Publikationsdatum
30.08.2022
Verlag
Springer US
Erschienen in
GeoInformatica / Ausgabe 3/2023
Print ISSN: 1384-6175
Elektronische ISSN: 1573-7624
DOI
https://doi.org/10.1007/s10707-022-00477-y

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