Electronics (Oct 2020)

Neural Network-Based Aircraft Conflict Prediction in Final Approach Maneuvers

  • Rafael Casado,
  • Aurelio Bermúdez

DOI
https://doi.org/10.3390/electronics9101708
Journal volume & issue
Vol. 9, no. 10
p. 1708

Abstract

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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.

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