Building trustworthy, explainable,
and accountable CCAM technologies
Connected and Cooperative Automated Mobility (CCAM) solutions are increasingly present in vehicle technologies, which benefit from artificial intelligence (AI) through AI-based perception, situational awareness, and decision-making components.
But AI can be unfair, biased, and can be extremely sensitive to unexpected inputs. Building explainable and trustworthy AI is the next mandatory step of technology development, incorporating among other equally important properties: robustness, privacy, explainability,
News
AIthena Project Final Event
The Athena project will conclude with a final event in Brussels on 2 October 2025. This event will celebrate the end of an exciting AI and technology journey for Connected, Cooperative and Automated Mobility (CCAM), showcasing the project's accomplishments and the...
AIthena project – ML DevOps tools for data governance and provenance
The AIthena project deliverable, D2.2, focuses on ML DevOps tools for data governance and provenance, and is titled "ML DevOps-oriented data lifecycle governance and provenance framework". The primary objective of Task 2.2 (within Work Package 2) is to develop...
Summary of the AITHENA 3rd Practitioners’ Workshop
AIthena Practitioners' Workshop – “How Can AI Revolutionise Road Transport?” Date: 15 May 2025. Location: EUCAD 2025, Joint Research Centre (JRC) – Ispra. The third AIthena practitioners' workshop was held in a hybrid format during the EUCAD 2025 conference at the...