Methods and systems for trajectory forecasting with recurrent neural networks using inertial behavioral rollout

A device comprising:

• a memory that stores a prediction model trained to predict future trajectories of objects, the prediction model trained over a first prediction horizon selected to encode inertial constraints in a predicted trajectory and over a second prediction horizon selected to encode behavioral constraints in the predicted trajectory;
• and
• a processor coupled to the memory and configured to:
• generate a planned trajectory of an autonomous vehicle, the generating comprising:
• receiving state data corresponding to the autonomous vehicle;
• receiving perception data corresponding to an object;
• predicting, using the prediction model, a future trajectory of the object based on the perception data;
• and
• generating the planned trajectory of the autonomous vehicle based on the future trajectory of the object and the state data.

A non-transitory computer readable medium that stores instructions that, when executed by a computing device, cause the computing device to execute a method, the method comprising:

• obtaining a prediction model trained to predict future trajectories of objects, the prediction model trained over a first prediction horizon selected to encode inertial constraints in a predicted trajectory and over a second prediction horizon selected to encode behavioral constraints in the predicted trajectory;
• and
• generating a planned trajectory of an autonomous vehicle, the generating comprising:
• receiving state data corresponding to the autonomous vehicle;
• receiving perception data corresponding to an object;
• predicting, using the prediction model, a future trajectory of the object based on the perception data;
• and
• generating the planned trajectory of the autonomous vehicle based on the future trajectory of the object and the state data.