COntroller adaptive Digital Assistant

Air traffic control is reputed as one of the five most stressful professions there is. Addressing the mental workload of controllers is therefore an important area of SESAR research and innovation and one that can be addressed using artificial intelligence. The project aims to develop a digital assistant capable of predicting future traffic, and assessing controllers’ stress levels and attention span, and whether they would be capable of handling the anticipated workload. The assistant would decide how to act, following an adaptation strategy: it may, for instance, increase the level of automation, enable additional AI-based tools, or request changes to the airspace (sector splitting).

The strategic objective of the project is to develop a system in which tasks are performed collaboratively by hybrid human-machine teams and dynamically allocated through adaptive automation principles. This will increase the efficiency, capacity, and safety of ATM, maximizing Human-AI teaming.