PRYSTINE aimed to deliver a fail-operational sensor-fusion framework at the component level, reliable embedded E/E architectures, and safety-compliant integration of Artificial Intelligence (AI) methods for object recognition, scene understanding, and decision-making within automotive applications.

PRYSTINE strived to actualize Fail-operational Urban Surround perceptION (FUSION) using robust Radar and LiDAR sensor fusion and control functions, thus enabling safe automated driving in urban and rural environments.

Over the course of the project, consortium partners produced 30 demonstrators, that showcased the technological developments of the project. Public demonstrators are available online on the project website.