As Europe moves toward climate neutrality by 2050, the integration of hydrogen-powered, electric, and hybrid-electric aircraft presents new challenges for current Air Traffic Management (ATM) and airport systems. These aircraft exhibit distinct performance profiles, requiring adaptive tools and metrics to ensure safe, efficient, and sustainable operations. NEXTAIR proposes an AI-driven optimisation framework, centred on evolutionary algorithms, to address these emerging complexities. The project focuses on dynamically modelling operational impacts such as taxiing, refuelling, boarding time, and noise emissions through the generation of tailored Key Performance Indicators (KPIs) for next-generation aircraft.

To compensate for the current lack of real-world data, NEXTAIR will employ synthetic data generation techniques supported by reference datasets such as base of aircraft data (BADA), enabling robust AI model training, simulation, and validation.

The project is fully aligned with the recommendations of the Alliance for Zero-Emission Aviation (AZEA) , supporting European policy goals by promoting a data-driven, safety-conscious, and environmentally sound integration of future aircraft into the aviation ecosystem.