AIthena consortium meeting in Graz

AIthena consortium meeting in Graz

The AIthena project (AI-Based CCAM: Trustworthy, Explainable, and Accountable) is contributing to the creation of an Explainable AI (XAI) in Cooperative, Connected and Automated Mobility (CCAM) development and testing frameworks by exploring three main AI pillars:...
AIthena D3.2 Report on initial AI algorithm development

AIthena D3.2 Report on initial AI algorithm development

Development of trustworthy and explainable AI algorithms in CCAM What AI algorithms are being developed in the AIthena project to advance autonomous vehicle technology and deployment? What are the challenges faced in developing these algorithms? Autonomous vehicles...
AIthena D2.3 Privacy-preserving methods

AIthena D2.3 Privacy-preserving methods

Addressing Data Privacy in CCAM What kind of data do cars collect? How does AI use data in cars? What privacy measures are in place and what are the researchers in the AIthena project proposing? Today’s vehicles collect large amounts of data, such as vehicle...
AIthena D3.1 Life cycle management framework for ML models

AIthena D3.1 Life cycle management framework for ML models

Standardisation of AI machine learning model cards in CCAM What is a machine learning model? How are AI algorithms standardised? And how does the AIthena project ensure accountability, trustworthiness, and ethical principles and standards in CCAM? Machine learning...