Carlos Luján

Carlos Luján, an industrial engineer from Universitat Politècnica de Catalunya (UPC), has more than 15 years in the field of vehicle homologation. He joined Applus+ Idiada in 2007 as a homologation engineer for commercial vehicles and is currently head of department for the homologation of connected and automated vehicles. He participates, among other forums, in the group of experts on automated and autonomous vehicle of the UNECE and leads Applus Idiada's R&D activities in the field of regulatory requirements for new CAV technologies.

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Presentation

Toward AI-driven automated driving systems: homologation perspective

AI-driven systems introduce dynamic learning, adaptability and continuous updates, posing significant challenges to traditional homologation methods. The objective of this paper is to analyze the existing homologation methodologies, such as the New Assessment/Test Methodology (NATM), and examine how various institutions, including UNECE, JRC and SAE, address AI's incorporation into ADS certification. The discussion focuses on identifying gaps in current frameworks, evaluating the harmonization of principles like transparency, robustness and ethical accountability, and proposing a roadmap for future integration. Ultimately, the paper aims to highlight how harmonized approaches can ensure both innovation and safety in AI-enabled ADS.