Among the actual trends that will affect society in the coming years, autonomous driving stands out as having the potential to disruptively change the automotive industry as we know it today. As a consequence, this will also highly impact the semiconductor industry and open new market opportunities, since semiconductors play an indispensable role as enablers for automated vehicles. Fully automated driving has been identified as one major enabler to master the Grand Societal Challenges of safe, clean, and efficient mobility. For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain in order to handle safety-critical situations by its own, which currently is not reached with state-of-the-art approaches also due to missing reliable environment perception and sensor fusion.

PRYSTINE will 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.

Furthermore, PRYSTINE will strengthen and extend traditional core competencies of the European industry, research organizations, and universities in smart mobility and in particular in the electronic component and systems and cyber-physical systems domain.

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 electrical/electronic (E/E) architecture enabling FUSION-based automated vehicles
4. Fail-operational systems for urban and rural environments based on FUSION

Objective 1: Components – Enhanced reliability and performance, cost and power of FUSION components

25% less data communication required compared to state-of-the-art
30% less false-positive detections compared to separate sensing approach
Fail-operational sensor compound vs. fail silent individual sensing approaches
Power reduction of 25% through semiconductor material improvements and functional convergence in sensor modules
Up to 30% cost reduction and 10% margin improvement for perception sub-systems

Objective 2: System – Dependable embedded control by co-integration of signal processing and AI approaches for FUSION

Fail-operational system approach for ADF (SAE Level 3+) vs. fail silent advanced driver assistance system (ADAS) approaches (SAE Levels up to 2)
Proposed Certification Approach for AI based sensor fusion, diagnostic, and control
Objective 3: Architecture – Dependable embedded control by cointegration of signal processing and AI approaches for FUSION
Fail-operational system architecture demonstrator for ADF (SAE Level 3+) vs. fail silent ADAS approaches (SAE Levels to 2)
LiDAR / RADAR sensor compound demonstrator

Objective 4: Automated Driving – Fail-operational systems for urban and rural environments based on FUSION

Demonstrators for fail-operational SAE Level 3+ ADFs in urban environments

Objective 5: Competitive advantage for European industry

Increasing market share and revenue of European companies through PRYSTINE’s ground-breaking technological advancements (O1-O4)

Objective 6: Increased user acceptance of automated driving functions