Scalable and agnostic safety frameworks

DriveSafeAI will develop the evidence base for an AI safety assurance framework that is scalable to different Operational Design Domains (ODDs). Pioneering the novel OASISS (ODD-based AI Safety In Self-Driving Systems) approach, these methods can be easily adapted to new ODDs, ensuring straightforward verification and validation of AI-based software across different regions and deployment geographies.

The methodologies developed will benefit the entire self-driving industry, supporting all system architectures that use AI, either in discrete components or fully end-to-end.

Novel simulation techniques for scenario testing

Using Wayve’s novel simulation techniques, DriveSafeAI will develop realistic and diverse edge-case scenarios that are challenging to test in real-world conditions. An ODD and behaviour-based scenario training and testing approach will be created, enabling the practical testing and development of DriveSafeAI’s methods using simulation methods. The use of simulation is crucial in safety testing for Automated Driving Systems to ensure breadth and diversity of scenario coverage that is simply not possible based on real-world testing alone. However, proving the correlation between your testing results in simulation and those you would expect to achieve in the real world is a topic of ongoing research across the industry, which DriveSafeAI is building an evidence base to inform guidance and best practice.