New Search

Advanced search
Export article
Open Access

Neural Network-Based Aircraft Conflict Prediction in Final Approach Maneuvers

Sciprofile linkRafael Casado, Sciprofile linkAurelio Bermúdez
Published: 18 October 2020
 by  MDPI
Electronics , Volume 9; doi:10.3390/electronics9101708

Abstract: Conflict detection and resolution is one of the main topics in air traffic management. Traditional approaches to this problem use all the available information to predict future aircraft trajectories. In this work, we propose the use of a neural network to determine whether a particular configuration of aircraft in the final approach phase will break the minimum separation requirements established by aviation rules. To achieve this, the network must be effectively trained with a large enough database, in which configurations are labeled as leading to conflict or not. We detail the way in which this training database has been obtained and the subsequent neural network design and training process. Results show that a simple network can provide a high accuracy, and therefore, we consider that it may be the basis of a useful decision support tool for both air traffic controllers and airborne autonomous navigation systems.
Keywords: neural networks / Multi-layer Perceptron (mlp) / Air Traffic Management (atm) / autonomous air navigation / conflict/collision detection and resolution (CD and R)

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

Share this article

Click here to see the statistics on "Electronics" .
References (20)
    Back to Top Top