What data do we need for training an AV motion planner?
Long Chen Lukas Platinsky Stefanie Speichert Błażej Osiński Oliver Scheel Yawei Ye Hugo Grimmett Luca Del Pero Peter Ondruska Long Chen Lukas Platinsky Stefanie Speichert Błażej Osiński Oliver Scheel Yawei Ye Hugo Grimmett Luca Del Pero Peter Ondruska
We investigate what grade of sensor data is required for training an imitation-learning-based AV planner on human expert demonstration. Machine-learned planners [1] are very hungry for training data, which is usually collected using vehicles equipped with the same sensors used for autonomous operation [1]. This is costly and non-scalable. If cheaper sensors could be used for collection instead, da...