This week we introduce next AIthena consortium partner: TNO

TNO is the independent Dutch organisation for applied research. TNO’s mission is to generate innovative solutions with demonstrable impact to achieve a safe, healthy, sustainable, and digital society and boost the earning power of the Netherlands.

At the Integrated Vehicle Safety Department of TNO we develop technology and assessment methodologies to accelerate the deployment of Connected and Cooperative Automated Mobility (CCAM) systems that contribute to ‘zero casualties’, ‘zero emissions’ and ‘zero loss’. We support industries and policymakers in the innovation process of smart vehicles and complex CCAM systems that help improve our mobility and logistics.

What is the role of TNO and the team in the project?

TNO, being the RTO, contributes to the AIthena project with research and development of Hybrid AI system for situation awareness. Situation awareness describes the readiness of the system to make good decision. It encompasses context (what behaviour is expected from the system in the current context?), competence (am I trained to deal with the current situation?) and risk (what is the risk of my actions in the current situation?). By combining knowledge-based AI with data-driven AI, this system can reason about its own readiness to make decisions in the current situation. The situation awareness is subsequently used in the planning of the actions of the vehicle (i.e., decision making process).

What are you currently working on in the project?

TNO team strives to develop algorithms and methods to monitor the correct behaviour of deployed vehicles equipped with automated driving capabilities. To achieve this ambitious goal, interrelated modules of an AI-based system need to be properly developed and tested.

Within the AIthena project, the TNO team focuses on the development of the situation awareness module within Work Package 3, as it enables the evaluation of the readiness of the AI-based system for decision making. In addition to the technology development, the proposed solution will be tested within the use-case demonstrators in Work Package 5. This is done by scenario-based verification, that proves the correct performance of the entire system working together.

From your perspective, how do you see the contribution of the AIthena project to building trustworthy, explainable, and accountable AI-based CCAM?

AIthena addresses the main barriers hindering wide adoption of AI-based CCAM systems. The human-centric approach and focus on trustworthiness and explainability aspects of AI are key to ensuring acceptance of human users. At the same time facilitating reliable testing of AI systems is needed to enable certification of such CCAM systems. Finally, addressing those problems via a European research project ensures, that we do not end up in a vendor locked-in solution and instead develop an open and widely available approach.

You can read more about the Integrated Vehicle Safety Department of TNO at Integrated Vehicle Safety and Smart Vehicles | TNO.