Programmable Systems for Intelligence in Automobiles

The ambition of PRYSTINE is to strengthen and to extend traditional core competencies of the European industry, research and universities in smart mobility and in particular the electronic component and systems and cyber-physical systems domains. PRYSTINE's target is to realize Fail-operational Urban Surround perceptION (FUSION) which is based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. Therefore, PRYSTINE's high-level goals are:

1. Enhanced reliability and performance, reduced cost and power of FUSION components
2. Dependable embedded control by co-integration of signal processing and AI approaches for FUSION
3. Optimized E/E architecture enabling FUSION-based automated vehicles
4. Fail-operational systems for urban and rural environments based on FUSION

PRYSTINE will deliver (a) fail-operational sensor-fusion framework on component level, (b) dependable embedded E/E architectures, and (c) safety compliant integration of Artificial Intelligence (AI) approaches for object recognition, scene understanding, and decision making within automotive applications. The resulting reference FUSION hardware/software architectures and reliable components for autonomous systems will be validated in in 22 industrial demonstrators, such as:

1. Fail-operational autonomous driving platform
2. An electrical and highly automated commercial truck equipped with new FUSION components (such as LiDAR, Radar, camera systems, safety controllers) for advanced perception
3. Highly connected passenger car anticipating traffic situations
4. Sensor fusion in human-machine interfaces for fail-operational control transition in highly automated vehicles

PRYSTINE’s well-balanced, value chain-oriented consortium, is composed of 60 project partners from 14 different European and non-European countries, including leading automotive OEMs, semiconductor companies, technology partners, and research institutes.