The complexity of the traffic situation increases every day, the demanding performance to comply with and the increasing digitalisation add new issues to air traffic management (ATM) services requiring new approaches. New tools have been prototyped to assist controllers by automating specific tasks, on turn the disruptive effectiveness of AI in learning from humans and benefiting from human experience and historical data opens new perspectives in assistance in tasks such as detection, resolution, prediction and optimisation, paving the way to a new generation of AI-based assistants. At the same time, the introduction of AI and the level of automation in air traffic controller life pose interesting challenges to face.

What the solution is about: This solution faces for the first time the concept of a digital assistant for air traffic controller (ATC-DA) – what is it? Which role in ATM architecture?
It aims at defining ATC-DA at a conceptual level, providing at the same time, at a higher level of maturity, its capabilities in cooperating with the controller in specific tasks. Four specific capabilities are demonstrated at TRL4 – tactical conflict revolver, identification of tactical opportunities, short-term traffic forecasting, flight plan correction.

Tactical conflict revolver provides the tactical conflict resolution advice. Tactical opportunity recommender monitors the traffic and identifies possible tactical opportunities to save fuel and assess the impact on the surrounding traffic. Advanced short-term forecaster enhances the prediction of sector demand 8 hours before, benefiting from historical data. Flight plan correctors check and correct flight plans and update them silently.
Tasks apply to pre-tactical phase and to tactical phase, considering the operating environment of en-route and TMA in medium- and high-density traffic.

New standards could be required to operate and interoperate the ATC-DA. Furthermore, based on AI, the ATC-DA may provide relevant insights in human-AI teaming, AI design assurance, and data infrastructure needs, potentially addressing further use cases for EASA studies.


BENEFITS 

• Decrease in fuel burn during the flight
• Improve Conflict Resolution Effectiveness
• Improve Time to solve the conflicts
• Increase Controller productivity
• Enhance the view on the demand to improve capacity and flow management in a pre-tactical level