Unreliable detection of environmental hazards and vehicle types leads to navigation failures. Improving recognition accuracy ensures safety in autonomous driving scenarios.

Signal interference and motion blur prevent reliable tracking of moving targets across diverse sensing modalities. Resolving this ensures data integrity in high-velocity monitoring environments.

Discrepancies between raw sensor data and physical reality lead to unreliable data processing. Standardizing these inputs ensures precise information sharing across distributed vehicle networks.