Evaluating Autonomous Vehicle Algorithms

The present invention extends to methods, systems, and computer program products for evaluating autonomous vehicle algorithms. Aspects use (e.g., supervised) machine learning techniques to analyze performance of autonomous vehicle algorithms on real world and simulated data. Machine learning techniques can be used to identify scenario features that are more likely to influence algorithm performance. Machine learning techniques can also be used to consolidate insights and automate the generation of relevant test cases over multiple iterations to identify error-prone scenarios.