Animikh Aich

Scalable Offline Metrics for Autonomous Driving

Real-World evaluation of perception-based planning models for robotic systems, such as autonomous vehicles, can be safely and inexpensively conducted offline, ı.e., by computing model prediction error over a pre-collected validation dataset with ground-truth annotations. However, extrapolating from