Title :
Neural network apply to predict aircraft trajectory for conflict resolution
Author :
Kaidi, R. ; Lazaar, M. ; Ettaouil, M.
Author_Institution :
Fac. of Sci. & Technol., Modeling & Sci. Comput. Lab., Sidi Mohammed Ben Abdellah Univ., Fez, Morocco
Abstract :
Today, Air Traffic keep increasing, for this raison, many research programs focus on collision avoidance technique. Aircraft trajectory prediction is a critical issue for Air Traffic Management (ATM). A safe and efficient prediction is a prerequisite for the implementation of automated tools that detect and solve conflicts between trajectories. Moreover, regarding the safety constraints, it could be more reasonable to predict intervals rather than precise aircraft positions. This paper a twofold objective; the first one, we develop an approach based on Artificial Neural Networks (ANNs), called Optimization of Multilayer Perceptron Architecture (OMPA), the second one, we use this approach to forecast trajectory in vertical plane to solve conflicts between two aircrafts in airspace.
Keywords :
aerospace computing; air traffic control; collision avoidance; control engineering computing; multilayer perceptrons; traffic engineering computing; trajectory optimisation (aerospace); ANN; ATM; OMPA; air traffic management; aircraft trajectory prediction; artificial neural networks; collision avoidance technique; conflict detection; conflict resolution; optimization-of-multilayer perceptron architecture; safety constraints; trajectory forecasting; Aircraft; Atmospheric modeling; Multilayer perceptrons; Neurons; Nonhomogeneous media; Trajectory; Air Traffic Management(ATM); Artificial Neural Netork (ANNs); Collision Avoidance; Optimization Multilayer Perceptron Architecture (OMPA);
Conference_Titel :
Intelligent Systems: Theories and Applications (SITA-14), 2014 9th International Conference on
Conference_Location :
Rabat
Print_ISBN :
978-1-4799-3566-6
DOI :
10.1109/SITA.2014.6847309