Collision avoidance using neural networks learned by genetic algorithms

Abstract

International audience; As Air Traffic keeps increasing, many research programs focus on collision avoidance techniques. In this paper, a neural netwok learned by genetic algorithm is introduced to solve conflicts between two aircrafts. The learned NN is then tested on different conflicts and compared to the optimal solution. Results are very promising.

Original document

The different versions of the original document can be found in:

• https://hal-enac.archives-ouvertes.fr/hal-00937688,

https://hal-enac.archives-ouvertes.fr/hal-00937688/document,

https://hal-enac.archives-ouvertes.fr/hal-00937688/file/569.pdf