LEARNING AIRCRAFT BEHAVIOR FROM REAL AIR TRAFFIC

摘要

EVAA is using machine learning, multi agent systems and real trajectories observation to generate behaviors of aircrafts. Since those behaviors are based on what happen in the real world, the resulting trajectories will be very realistic. It is also possible to simulate supervised aircrafts, which will follow their flight plan (or the orders of a pseudo-pilot). This enables EVAA to be usable in many situations such as pilot and controller training, generating autonomous surrounding traffic generation, fully human-controlled traffic, or any combination you can imagine.