Introspective Failure Prediction for Autonomous Driving Using Late Fusion of State and Camera Information

We present an introspective failure prediction approach for autonomous vehicles. In autonomous driving, complex or unknown scenarios can cause a disengagement of the self-driving system. Disengagements can be triggered either by automatic safety measures or by human intervention. We propose to use recorded disengagement sequences from test drives as training data to learn to predict future failure...