Automated driving (AD) had the potential to significantly reduce the number of fatalities and severely injured in road traffic. With StreetProof, TNO develops requirements for how automated vehicles should drive alongside human road users, together with its associated implementation and testing methodologies.
Scaled monitored deployment
We develop algorithms and methods to monitor the correct behavior of deployed vehicles equipped with automated driving capabilities, for both testing and assessment purposes. This concept extends current EDRs to include vehicle health, vehicle driving behavior and traffic behavior. We validate and demonstrate this concept with our CarLabs and StreetLive system.
To make sure that automated vehicles interact safely and comfortably with their drivers, we develop models for driver state estimation, situational awareness, motion sickness and context awareness. Next to that, TNO specializes in algorithms to ensure a safe transition of control and optimal driver interaction in various ODDs.
Safe & Social driving
Because driving is a social activity mediated by technology, automated vehicles should display a driving style that is acceptable for human road users. To achieve this Safe & Social driving style, design guidelines are necessary on how to achieve human-like behavior. At TNO, we develop a framework to extract these guidelines from different sources of driving data and convert them into technical requirements.