The aviation industry is making major investments in advanced automation and AI, widely seen as key enablers for safer, more resilient, sustainable, and efficient operations across the sector. Yet, designing and deploying these next-generation systems comes with complex challenges. The unique characteristics of these technologies demand a fundamental rethink of existing regulatory and validation frameworks—requiring a shift away from traditional approaches to enable faster, yet robust, pathways from research to real-world deployment.

HUCAN is a holistic and iterative design approach that progressively integrates strategic certification objectives and requirements, as defined by EASA for AI, from the early stages of developing highly automated ATM systems. The approach is tailored to support SESAR projects within both exploratory and industrial research frameworks. HUCAN encompasses multiple dimensions—concept design, technical assurance (including safety and security), human factors, ethics, and liability—ensuring a comprehensive treatment of the challenges posed by AI integration. By aligning design goals with regulatory compliance from the outset, HUCAN facilitates the contextualization of certification requirements, enabling their effective fulfilment by the end of the development cycle. This reduces the risk of late-stage rework, accelerates time-to-market, and supports the deployment of safe, trustworthy, and efficient ATM innovations.

This approach addresses the key performance areas (KPAs) identified in the EASA AI Roadmap 2.0 and its supporting Concept Papers. It also considers the general provisions and strategic directions introduced by the AI Act (Reg. (EU) 2024/1689) for the implementation of the new requirements related to high-risk AI systems in aviation (especially Article 108).

BENEFITS

• Reduce the gap between the research and the time to market
• Foster homogeneity of approach among projects
• Exploit synergies between research and certification