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],
: [https://hal-enac.archives-ouvertes.fr/hal-00937688/document https://hal-enac.archives-ouvertes.fr/hal-00937688/document],
: [https://hal-enac.archives-ouvertes.fr/hal-00937688/file/569.pdf https://hal-enac.archives-ouvertes.fr/hal-00937688/file/569.pdf]