Towards Explainable Automation for Air Traffic Control Using Deep Q-learning from Demonstrations and Reward Decomposition

The current ATC system is seen as the most significant limitation to coping with an increased air traffic density. Transitioning towards an ATC system with a high degree of automation is essential to cope with future traffic demand of the airspace. In recent studies, reinforcement learning has shown promising results automating Conflict...

Exploring reinforcement learning methods for autonomous sequencing and spacing of aircraft

Research on reinforcement learning algorithms to play complex video games have brought forth controllers surpassing human performance. This paper explores the possibilities of applying these techniques to the sequencing and spacing of aircraft. Two experiments are performed. First a single aircraft must learn to fly a 4D trajectory using only...