Method and system for developing autonomous vehicle training simulations

A computer program product comprising:

• a memory that stores programming instructions that are configured to cause a processor to train a vehicle motion planning model by:
• receiving, from a first data store containing a plurality of simulation scenarios, a base simulation scenario that includes features of a scene through which a vehicle may travel,
• generating an augmentation element that comprises a simulated behavior for an object in the scene by:
• accessing a second data store in which behavior probabilities are mapped to object types to retrieve a set of behavior probabilities for the object;
• and
• applying a randomization function to the behavior probabilities to select the simulated behavior for the object;
• adding the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario, and
• applying the augmented simulation scenario to an autonomous vehicle motion planning model to train the motion planning model by, in the augmented simulation scenario:
• simulating movement of the vehicle along a planned trajectory;
• by the motion planning model, in response to a perception system of the vehicle detecting the augmentation element, selecting a continued trajectory for the vehicle, wherein the continued trajectory is either the planned trajectory or an alternate trajectory;
• and
• causing the vehicle to move along the continued trajectory.

A vehicle motion planning model training system, comprising:

• a processor;
• a first data store containing a plurality of simulation scenarios;
• and
• a memory that stores programming instructions that are configured to cause the processor to train a vehicle motion planning model by:
• receiving, from the first data store, a base simulation scenario that includes features of a scene through which a vehicle may travel,
• generating an augmentation element that comprises a simulated behavior for an object in the scene by:
• accessing a second data store in which behavior probabilities are mapped to object types to retrieve a set of behavior probabilities for the object;
• and
• applying a randomization function to the behavior probabilities to select the simulated behavior for the object,
• adding the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario, and
• applying the augmented simulation scenario to an autonomous vehicle motion planning model to train the motion planning model by, in the augmented simulation scenario:
• simulating movement of the vehicle along a planned trajectory;
• by the motion planning model, in response to a perception system of the vehicle detecting the augmentation element, selecting a continued trajectory for the vehicle, wherein the continued trajectory is either the planned trajectory or an alternate trajectory;
• and
• causing the vehicle to move along the continued trajectory.