Background
An automotive company was validating perception systems for self-driving cars.
Testing Complexities
- Non-deterministic model behavior
- Edge case identification
- Real-world scenario simulation
- Safety-critical failure modes

Testing Framework
Simulation Testing
- 10M+ miles of virtual driving
- Corner case scenario generation
Optimization Statistics
Hardware-in-the-Loop
- Sensor fusion validation
- Timing and latency testing
Real-World Testing
- Controlled environment validation
- Shadow mode driving
Key Metrics
- False positive/negative rates
- Object classification accuracy
- Decision latency
Results
- Achieved 99.9999% reliability
- Reduced edge case failures by 82%
- Validated safety in 100+ scenarios