The CODA project aimed to develop a digital assistant that supports air traffic controllers by predicting future traffic and assessing their mental workload, attention, stress, and ability to handle anticipated tasks. The system adapts by increasing automation, enabling AI-based tools, or adjusting airspace management (e.g., sector splitting) based on real-time and predicted operator status. The system integrates state-of-the-art technologies, including:

- Prediction models to forecast controller activities and their impact on human performance;

- Neurophysiological assessment to measure workload, attention, stress, fatigue, and vigilance;

- Adaptive automation to dynamically guide task allocation between the controller and digital assistant, based on cognitive complexity.

The project leveraged AI-based, adaptable, and explainable systems to ensure safety and performance, optimising human-machine interaction through a Human Machine Performance Envelope.