Patent ID: 11858536
Assignee: UATC, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC B  G | IPC B  G

Claim 0:
1. A computer-implemented method, comprising:
(a) obtaining sensor data descriptive of an environment of an autonomous vehicle, the sensor data descriptive of a plurality of objects within the environment;
(b) determining, using a machine-learned model framework comprising one or more machine-learned models, a joint probability distribution by, for each respective object of the plurality of objects:
(i) generating a respective plurality of object trajectories by:
determining an estimated heading for the object; and
for each object trajectory of the respective plurality of object trajectories, generating the object trajectory from the estimated heading by sampling a trajectory mode from a plurality of trajectory modes and sampling a value for a trajectory control parameter from a range of values associated with the trajectory control parameter; and

(ii) determining a plurality of probabilities respectively for the respective plurality of object trajectories, the plurality of probabilities conditioned on a respective potential vehicle motion trajectory of a plurality of potential vehicle motion trajectories of the autonomous vehicle; and

(c) determining, using the machine-learned model framework and from among the plurality of potential vehicle motion trajectories, a target vehicle motion trajectory for the autonomous vehicle based at least in part on the joint probability distribution;
wherein the one or more machine-learned models were trained based on a loss determined over a subset of the plurality of object trajectories, the subset configured to exclude one or more of the object trajectories that are within a tolerance distance of a corresponding ground truth object trajectory.