SafeWahr tackled a key challenge in autonomous driving: ensuring the safety and reliability of AI-based perception systems. Our team developed the Situation Monitor and Function Monitor, crucial for assessing vehicle safety and responding to new driving situations.
Special thanks to our incredible team at the Dependable and Autonomous Cyber-Physical Systems (DACS) group at ISSE, TU Clausthal. Your dedication was instrumental in our success. We also extend our gratitude to AVL for hosting, and to our partners Deep Safety, Intel Deutschland, STTech, Validas AG, TÜV Rheinland, and the Federal Ministry for Economic Affairs and Climate Action (BMWK) for their support.
Explore our research on ResearchGate:
- Autoencoder-Based Semantic Novelty Detection: Towards Dependable AI-Based Systems
- Connected Dependability Cage Approach for Safe Automated Driving
- Towards Exploring Adversarial Learning for Anomaly Detection in Complex Driving Scenes
- A Method for Runtime Validation of AI-based Environment Perception in Automated Driving Systems
We are grateful to everyone who contributed to the success of the SafeWahr project and to all those who supported us along the way. Stay tuned for more exciting innovations and breakthroughs arising from this significant accomplishment!
