Systems and methods related to training a machine learning model used in controlling autonomous vehicle(s)

Abstract

Systems and methods related to controlling an autonomous vehicle ('AV') are described herein. Implementations can obtain a plurality of instances that each include input and output. The input can include actor(s) from a given time instance of a past episode of locomotion of a vehicle, and stream(s) in an environment of the vehicle during the past episode. The actor(s) may be associated with an object in the environment of the vehicle at the given time instance, and the stream(s) may each represent candidate navigation paths in the environment of the vehicle. The output may include ground truth label(s) (or reference label(s)). Implementations can train a machine learning (“ML”) model based on the plurality of instances, and subsequently use the ML model in controlling the AV. In training the ML model, the actor(s) and stream(s) can be processed in parallel.