The verification challenge for autonomous driving systems lies not only in the algorithms themselves, but in whether the perception system remains reliable under rain, fog, backlight, contamination, and extreme scenarios. Real-world road testing is costly and struggles to cover long-tail cases, so simulation plays an increasingly important verification role.
Industry Characteristics
- Pronounced coupling among perception, control, and complete vehicle systems
- High safety requirements with significant long-tail scenario verification pressure
- Sensor performance highly susceptible to environmental influence
Key Topics
- Perception degradation analysis of cameras, radar, and LiDAR under adverse weather
- Assessment of sensor mounting position and occlusion effects
- Verification of contamination, icing, and thermal management impacts on performance
- Propagation analysis of perception errors into control strategies
Recommended Approach
Autonomous driving simulation should connect virtual scenarios, sensor physics models, and the full vehicle decision chain, rather than remaining at the algorithm replay level. Only by understanding how the physical world affects perception inputs can verification results more closely reflect real-world risks.
Business Significance
The core value of this type of solution is expanding verification coverage within a controllable cost while exposing system weaknesses in complex scenarios as early as possible.