Optimizing B-splines using Genetic Algorithms Applied to Air-traffic Conflict Resolution

Clément Peyronne 1, 2 Daniel Delahaye 1 Marcel Mongeau 3 Laurent Lapasset 4
1 ENAC - Ecole Nationale de l'Aviation Civile
2 Capgemini [Toulouse]
3 MAIA-OPTIM - ENAC Equipe MAIAA-OPTIM
MAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien
4 Capgemini
Capgemini [Toulouse]
Abstract : Conflict resolution has always been a sensitive matter in air-traffic management. Current European projects aim partial or total automation of air traffic control to deal with the constant growth of air traffic. Technological advances on flight management system allows us to consider an automatic conflict resolution using continuous trajectories. In this paper, we present a new methodology that, first, relies on B-splines to model trajectories, secondly models air-traffic conflict resolution as an optimization problem whose decision variables are the spline control points. Finally, we use genetic algorithms to tackle this optimization problem in order to generate optimal conflict-free situations.
Keywords : genetic algorithms B-splines air-traffic conflict resolution
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Conference papers
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Clément Peyronne, Daniel Delahaye, Marcel Mongeau, Laurent Lapasset. Optimizing B-splines using Genetic Algorithms Applied to Air-traffic Conflict Resolution. ICEC 2010, International Conference on Evolutionary Computation, Oct 2010, Valencia, Spain. pp 213-218; ISBN: 978-989-8425-31-7, ⟨10.5220/0003082802130218⟩. ⟨hal-00987459⟩

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