  Commonly used metrics for evaluation of object detection systems (precision,
recall, mAP) do not give complete information about their suitability of use in
safety critical tasks, like obstacle detection for collision avoidance in
Autonomous Vehicles (AV). This work introduces the Risk Ranked Recall ($R^3$)
metrics for object detection systems. The $R^3$ metrics categorize objects
within three ranks. Ranks are assigned based on an objective cyber-physical
model for the risk of collision. Recall is measured for each rank.

Robotics;Artificial Intelligence;Machine Learning