Project Details


Connected, Cooperative and Automated Mobility (CCAM) solutions have emerged thanks to novel Artificial Intelligence (AI) which can be trained with huge amounts of data to produce driving functions with better-than-human performance under certain conditions. However, AI remains largely unexplored with respect to explainability, privacy preservation, ethics, and accountability. These features will establish the basis of trustworthy AI, as a novel paradigm to fully understand and trust AI in operation, while using it at its full capabilities for the benefit of society. AITHENA is contributing to the improvement of Explainable AI (XAI) in CCAM development and testing frameworks, researching three main AI pillars: data, models, and testing.


Project details

Duration 11/2022 - 10/2025



Project goal

AIthena aims to build trustworthy, explainable, and accountable CCAM technologies and to provide CCAM developers with guidance on ensuring that the CCAM functions they develop have the needs of people at their centre.


Demonstrators will show the AITHENA methodology in four use cases: 1) perception (what the AI perceives, and why), 2) situational awareness (what the AI understands about the current driving environment, including the driver state), 3) decision-making (why a certain decision is taken), and 4) traffic management (how transport-level applications interoperate with AI-enabled systems at vehicle level).

A human-centric methodology is being developed to derive the dimensions of trustworthy AI based on people's needs, concerns and expectations of CCAM applications. AITHENA will propose a set of indicators for Explainable AI and an analysis to explore trade-offs between these dimensions.

Role of Rupprecht Consult

Rupprecht Consult leads WP1, which is the methodology to support the development and testing of AI-based CCAM solutions in a way that is human centric. Within this task, Rupprecht Consult is also responsible for the chapter on assessing ethics and fairness in the development and testing of AI-based CCAM functions. Rupprecht Consult also leads the task around developing lessons learnt and policy recommendations.

Contact details

Bonnie Fenton
+49 173 726 3681

Project partners

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