Title :
3D airspace sector design by genetic algorithm
Author :
Sergeeva, Marina ; Delahaye, Daniel ; Mancel, Catherine
Author_Institution :
MAIAA Lab., French Univ. of Civil Aviation (ENAC), Toulouse, France
Abstract :
In recent years, special interest has been paid to the solution of sector design problem. The airspace is partitioned into sectors, each of them being controlled by a group of controllers. Airspace sectors should be designed cautiously, ensuring that no sector would be overloaded during the day. The objective of an airspace design process is to adapt the airspace according to the evolution of the traffic. The aim of the presented work is to propose a new global method for the sectorization of the European airspace based on a novel mathematical modeling of the airspace and heuristic optimization methods. The main purpose of this research is to develop a method for automatic airspace sectorization, which would be able to create operationally acceptable sectors.
Keywords :
air traffic; genetic algorithms; pattern clustering; 3D airspace sector design; European airspace; automatic airspace sectorization; genetic algorithm; heuristic optimization methods; mathematical modeling; Aircraft; Atmospheric modeling; Clustering algorithms; Complexity theory; Shape; Three-dimensional displays; Trajectory; airspace sector design; genetic algorithm; k-means clustering; sectorization;
Conference_Titel :
Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2015 International Conference on
Conference_Location :
Budapest
Print_ISBN :
978-9-6331-3140-4
DOI :
10.1109/MTITS.2015.7223300
