Customer Pain Points
Difficulty in Replicating Physical Sensor Characteristics
Sensor physical properties (e.g., noise, latency) are challenging to accurately simulate in software, affecting test authenticity.
Complex Scenarios Are Hard to Recreate
Complex scenarios (e.g., multi-sensor synchronous failures, extreme environmental interference) are difficult to reproduce in real-vehicle testing.
Insufficient Automation Hinders Regression Testing
Low automation levels in testing processes struggle to support large-scale regression testing required before mass production.
Solution Value
Authenticity & Controllability
Physics-based sensor signal chains with video/point cloud injection preserve real-world characteristics (noise, latency, thermal drift, jitter). Parametrically reproducible environmental interference (weather/lighting/occlusion) ensuring fully repeatable tests
Multimodal Consistency
Unified calibration of timestamps, spatial alignment, and bandwidth jitter across cameras/LiDARs/radars/IMUs. Quantifiable end-to-end latency and synchronization to prevent 'simulation success, real-world failure' scenarios
Closed-Loop Efficiency
Log→HIL data replay integrated with CI/CD pipelines. Automated regression testing with version difference analysis. Rapid issue reproduction→fixation→verification cycle
Comprehensive Coverage
One-stop validation for functional strategies, communication protocols (CAN/CAN FD/Ethernet/SOME-IP/DoIP), diagnostics. Fault injection (black screen/packet loss/sync failure/channel failure), resource stress, and degradation logic testing
Scalable Automation
Test case orchestration, batch concurrent execution, and automated judgment/report generation. Supports large-scale regression testing and baseline tracking for mass production
Engineering Adaptability
Compatible with mainstream domain controllers and multi-vendor sensor configurations. Customizable channels/topologies for rapid on-site deployment
