US 11,987,265 B1
Agent trajectory prediction using target locations
Hang Zhao, Sunnyvale, CA (US); Jiyang Gao, San Jose, CA (US); Chen Sun, Great Neck, NY (US); Yi Shen, Sunnyvale, CA (US); Yuning Chai, San Mateo, CA (US); Cordelia Luise Schmid, Saint Ismier (FR); Congcong Li, Cupertino, CA (US); Benjamin Sapp, Marina del Rey, CA (US); Dragomir Anguelov, San Francisco, CA (US); Tian Lan, Sunnyvale, CA (US); and Yue Shen, Mountain View, CA (US)
Assigned to Waymo LLC, Mountain View, CA (US)
Filed by Waymo LLC, Mountain View, CA (US)
Filed on Jul. 28, 2021, as Appl. No. 17/387,852.
Claims priority of provisional application 63/057,717, filed on Jul. 28, 2020.
Int. Cl. B60W 60/00 (2020.01); G06N 3/02 (2006.01)
CPC B60W 60/001 (2020.02) [G06N 3/02 (2013.01); B60W 2420/42 (2013.01); B60W 2554/4049 (2020.02)] 18 Claims
OG exemplary drawing
 
1. A method performed by one or more computers, the method comprising:
obtaining scene context data characterizing an environment, the scene context data comprising data that characterizes a trajectory of an agent in a vicinity of a vehicle in an environment up to a current time point;
identifying a plurality of initial target locations in the environment;
generating, for each of a plurality of target locations that each corresponds to one of the initial target locations, (i) a respective predicted coordinate offset between the target location and the corresponding initial target location and (ii) a respective predicted likelihood score that represents a likelihood that the target location will be an intended final location for a future trajectory of the agent starting from the current time point;
selecting a first subset of the target locations based on the respective predicted likelihood scores of the target locations;
for each target location in the first subset of the target locations, generating a predicted future trajectory for the agent that is a prediction of the future trajectory of the agent given that the target location is the intended final location for the future trajectory;
selecting, as likely future trajectories of the agent starting from the current time point, one or more of the predicted future trajectories; and
controlling the vehicle using the one or more selected predicted future trajectories.