Failing to learn: Autonomously identifying perception failures for self-driving cars
University of Michigan, July 26, 2018
One of the major open challenges in self-driving cars is the ability to detect cars and pedestrians to safely navigate in the world. Deep learning-based object detector approaches have enabled great advances in using camera imagery to detect and classify objects. But for a safety critical application such as autonomous driving, the error rates of the current state-ofthe-art are still too high to enable safe operation.