The automation of vehicles – ultimately aiming at fully autonomous driving – has been identified as one major enabler to master the Grand Societal Challenges “Individual Mobility” and “Energy Efficiency”. Highly automated driving functions (ADF) are one major step to be taken.
One of the major challenges to successfully realizing highly automated driving is the step from SAE Level-2 (Partial automation) to SAE Levels-3 (Conditional automation) and above. At level-3, the driver remains available as a fallback option in the event of a failure in the automation chain, or if the ADF reaches its operational boundaries. At higher levels, the driver cannot be relied upon to intervene in a timely and appropriate manner, and consequently, the automation must be capable of handling safety-critical situations on its own.
For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain. PRYSTINE's main 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.
The PRYSTINE project's strategy has consisted in achieving its main target through reaching four key technical objectives. While these four technical objectives address different levels (components, control systems, architectures and function) of the automation chain, PRYSTINE has also reached 2 non-technical objectives addressing market/social/technological impacts and “European Values”.
The objectives were:
Objective 1: Enhanced reliability and performance, cost and power of FUSION components
Objective 2: Dependable embedded control by co-integration of signal processing and AI approaches for FUSION
Objective 3: Optimized E/E architecture enabling FUSION-based automated vehicles
Objective 4: Fail-operational systems for urban and rural environments based on FUSION
Objective 5: Competitive advantage for European industry
Objective 6: Increased user acceptance of automated driving functions
In conclusion, the project has reached all its initial objectives and has been able to prove its achievement in a qualitative and quantitative manner.