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 to enable safe automated driving in urban and rural environments. Therefore, PRYSTINE's high-level goals are:
- Enhanced reliability and performance, reduced cost and power of FUSION components
- Dependable embedded control by co-integration of signal processing and AI approaches for FUSION
- Optimized E/E architecture enabling FUSION-based automated vehicles
- Fail-operational systems for urban and rural environments based on FUSION
PRYSTINE is ready to 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 22 industrial demonstrators.
Video 1: PRYSTINE SC2 Demo 2.2 Drive by Wire Car.
A novel approach to software component integration: developed COMPAGE framework (fail-operational system component management framework) and AI-based algorithms capable of identifying faulty sensors by analyzing data of different types, e.g. LIDAR, Radar, cameras.
Video 2: PRYSTINE SC2 Demo 2.3 Data Fusion and Fall back.
A fully integrated security engineering process for realizing secure autonomous driving and a trust model for evaluating the trustworthiness of sensors data with the data fusion module for improving the accuracy of object detection and tracking
Video 3: PRYSTINE SC2 Demo 2.4 Passenger Vehicle for Low Speed Autonomy.
Fusion algorithms and perception components to be utilized by SAE Level 3+ equivalent autonomous parking and low speed autonomy solutions (related to Automated Parking Vale Systems) providing fail-operationality and robustness by the utilization and fusion of multiple sensor sources including cameras and Radar.
Video 4: PRYSTINE SC3 Demo 3.1, 3.2, 3.3.
- Demo 3.1 E/E architecture demonstrator for automotive electronics enabling AD.
- Demo 3.2 Simulation, development and validation framework for fail-operational sensor-fusion E/E architecture
- Demo 3.3 Dynamically shaped, reliable mobile communication
Video 5: PRYSTINE SC7 Demonstrators 7.1, 7.2, 7.3
- Demonstrator #7.1: Shared control to study driver interaction with automated vehicles considering the driver state and the driving environment (DiL Simulator).
- Demonstrator #7.2: Traded control to study automatic transitions between different levels of automation in complex environments, while cooperating with a bus for enhanced perception (V2V).
- Demonstrator #7.3: Autonomous control to study AI-based decision algorithms for highly automated vehicles in highway and urban scenarios, considering a traffic state predicition network