Discover how Vayavya Labs' SOAFEE Cloud-to-Edge Blueprint enables virtual validation of autonomous driving stacks with behavioral parity & safety confidence.
The world is racing towards autonomous mobility. Most vehicle-level ADAS testing happens in a controlled test environment. This limits the test functional test coverage and does not expose the system to real-time scenarios. We are in need of Automated Test scenarios and Test setups, which can help run the tests without limitations. The new era of highly automated driving tasks requires soft tools and methods. To ensure wide coverage of real-life use cases, and should be reliable and robust.
Our testing, calibration, & validation capabilities offer reassurance under safe & flexible lab conditions. With a vast number of real-world driving situations & maneuvers.
We have created a range of tools that can be used for the development, & evaluation of perceived safety, comfort, & the overall driving experience.
The transition from the number of miles to quality of coverage for ADAS verification.
Tailor-fit your business needs- Customize for various regulations & industry standards.
Less HIL, Less expensive.
Scenario based Testing
Since simulation models are used, we can adapt more quickly to requirement changes. Faster testing. Less time to deliver.
Scenario Libraries for DUT stack verification
Support for different ADAS features and autonomy levels
Regulations & standards specific ( EURO NCAP, NHTSA) specific development
Development in OSC 1.x, OSC 2.0, or customer-specific input formats
Verification with various simulators like CARLA, Carmaker, Scanner, etc.
Support various industry-standard simulators.
Supports scenario libraries based on open source scenario 2.0
Coverage & KPI evaluation
Discover how Vayavya Labs' SOAFEE Cloud-to-Edge Blueprint enables virtual validation of autonomous driving stacks with behavioral parity & safety confidence.
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Introduction With the rapid advancement of technology, advanced driver assistance systems (ADAS) and autonomous vehicles (AVs) are evolving at an unprecedented pace.
By utilizing sophisticated models created through ASAM OpenScenario DSL, engineers can analyze the impact of inputs on Autonomous Vehicle Development.
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