Building Real-time Awareness of Out-of-distribution in Trajectory Prediction for Autonomous Vehicles
The episode discusses a paper on building real-time awareness of out-of-distribution (OOD) data in trajectory prediction for autonomous vehicles. Hosts discuss how existing models assume predictable behavior and propose changing the output contract to include uncertainty scores. The paper suggests integrating this OOD detection into the entire perception stack to improve AI safety and trust.