HL200 Data Replay Station

HIL DATA REPLAY STATION

Model: HL-200

Camera Injection: Paired with AXL1448 video injection board, supports up to 12-channel GMSL data injection, max resolution 8M (3840×2160) @30fps.


Radar Data Injection: Paired with TC1017 CAN bus simulation tool, supports up to 8-channel CAN/CANFD radar data injection.


Lidar Injection: Paired with TE1176 automotive Ethernet switch, supports up to 6-channel LiDAR data injection.


Ultrasonic Injection: Paired with HL-USE524.09, supports up to 12-channel ultrasonic radar data injection.


Bus Data Injection: Paired with TP1018 CAN bus injection board, supports up to 12-channel CAN/CANFD/LIN bus data injection.


ALG DATA REPLAY STATION is a critical device for autonomous driving data playback development and testing. It provides a controlled and secure testing platform, enabling development teams to inject various sensor data into specific domain controllers for debugging, optimization, and validation of functions and algorithms.




Product Advantages

■ Multi-Sensor Data Compatibility

Autonomous driving systems rely on various sensors (e.g., LiDAR, cameras, millimeter-wave radars) to acquire environmental data. The HL200 supports multiple sensor types and diverse data formats for playback.


■ Data Synchronization & Consistency

Achieves millisecond-level high-precision data synchronization for injection, ensuring data real-time performance as well as consistency in content, frame rate, and timing.


■ Stability Assurance

The HL200 is capable of stable operation for 5 x 24 hours continuously.


■ Multi-Scenario Applications

Designed to meet the hardware-in-the-loop (HIL) data playback testing needs of autonomous driving systems.





Typical Applications



■ Data Replay

Hardware-in-the-loop testing for intelligent driving controllers.


■ Function Activation and Stability Testing

Validating function activation and algorithm stability of intelligent driving controllers.


■ Real-Time and Reliability Verification

Testing the real-time performance and reliability of intelligent driving controller algorithms on actual hardware environments.


Title Release Date Published By Download