Led by DeepBlue (Sep. 2024 - Feb. 2026), this exploratory project focuses on improving air traffic management (ATM) through innovative human-AI collaboration and adaptive automation. The meeting included progress updates, planning for next steps, and testing of BrainSigns’ EEG device for neurophysiological analysis (hbrainsigns.com).

CODA aims to develop a digital assistant that predicts traffic patterns, assesses air traffic controllers' workload and attention, and dynamically adapts operational strategies using AI and automation. ENAC contributes to key areas, including concept definition, modeling, and user-centric interface design. With a target of reaching Technology Readiness Level 2 (TRL 2), CODA seeks to revolutionize hybrid human-machine teamwork in ATM.

Learn more: coda-sesar.eu