With advancements and increasing complexity of driver assistance systems, the efforts required for testing, verification and validation also increases. Theoretically each function in the vehicle has to work without failure and finally translate into no accidents until the end-oflife of the vehicle. To ensure this, we need new testing methods.
Billions of kilometers have to be successfully test driven in the realworld before autonomous vehicles are validated and finally released. In practice, this often proves to be difficult, since there is an exponential increase in the E/E features and the frequency of software releases is higher than ever before. Covering all tests for each release is time- and cost-intensive. Further main challenges in the industry are frequently changing development, test and validation, Big Data, Real-world complexity and agility in development. AI-Core offers tools and services that allow customer to handle these challenges and make validation efficient and practical.
AI-Core can process large data and initially extract the ground truth from the existing real data. Valid driving scenarios are classified from the real data and extracted into a database, therefore new test scenarios that focus on critical scenarios are generated.
Potential customer value
- High quality scenario classification, extraction directly from the real-world raw data
- Meta information can be added to the available Big Data and add the 5th ‚V‘ which is the Value
- Complies with ASAM standards such as OpenSCENARIO and planned extensions to upcoming OpenSCENARIO 2.0
- Creation of new scenarios based on system or test requirements or based on criticality with respect to the function under test
- Speeds up the test and validation process
- High quality and quantity annotation adjusts to changes in the specification with the capability to comply with upcoming standards such as OpenSCENARIO, OpenLABEL, etc.
- Tools and services offer industry independent solutions for cross domain applications:
- Data analysis
- HMI testing
- Data Anonymization and GDPR compliance
- Customer specific AI modules to address individual challenges
- Faster, agile, effective and seamless tests are possible for complex systems of ADAS and autonomous vehicles
- Efficient use of real-world big data, making the Big Data usable for test, verification and validation due to high quality and automated processes
- Saves 95% of time in scenario extraction, scenario classification, result analysis and annotation
- Improves quality and at the same time provides deterministic results with real-world Big Data
- Learning algorithms are used and hence reduces the efforts for standardization
- AI-Core supports and allows extensions to automated real-world proving ground extending the closed loop seamless scenario based testing from laboratory to the real-world