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 D5.1 Testing and evaluation methodology for AI-driven CCAM systems
Understanding how AI works: CCAM Edition AI has revolutionised Connected, Cooperative and Automated Mobility (CCAM) solutions by enabling AI models to be trained on vast amounts of data. However, AI remains underexplored in terms of explainability, privacy, ethics and...
AIthena at the Autonomous Main Event in Vienna
The AIthena project will be represented at the Autonomous Main Event 2024 by Georg Stettinger from Infineon Technologies AG. Georg Stettinger will present the AIthena project - AI-based CCAM: Trustworthy, Explainable and Accountable at the Autonomous Spotlight...
AITHENA: DATA – Life cycle management and generation
In the context of the AITHENA project, when it comes to making AI more trustworthy and human-centric, data management and privacy are at the heart of the issue. In Work Package 2 we have 3 different tasks that deal with the whole data lifecycle management and data...