US 11,932,282 B2
Vehicle trajectory control using a tree search
Timothy Caldwell, Mountain View, CA (US); Rasmus Fonseca, Boulder Creek, CA (US); Arian Houshmand, Mountain View, CA (US); Xianan Huang, Foster City, CA (US); Marin Kobilarov, Baltimore, MD (US); Lichao Ma, Santa Clara, CA (US); Chonhyon Park, San Jose, CA (US); Cheng Peng, Sunnyvale, CA (US); and Matthew Van Heukelom, San Francisco, CA (US)
Assigned to ZOOX, INC., Foster City, CA (US)
Filed by Zoox, Inc., Foster City, CA (US)
Filed on Aug. 4, 2021, as Appl. No. 17/394,334.
Prior Publication US 2023/0041975 A1, Feb. 9, 2023
Int. Cl. B60W 60/00 (2020.01); G05B 13/02 (2006.01)
CPC B60W 60/0027 (2020.02) [G05B 13/0265 (2013.01); B60W 2554/402 (2020.02); B60W 2554/4045 (2020.02)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving route data associated with a start position and an end position in an environment;
receiving sensor data from a sensor;
determining, based at least in part on the sensor data and the route data, a first candidate action for controlling motion of a vehicle;
determining a first cost associated with the first candidate action, the first cost being based at least in part on a lower bound cost, the lower bound cost being an estimate of a lowest cost of an action to alter a first state of the vehicle at a time associated with a beginning of the first candidate action;
determining, based at least in part on the first candidate action and the sensor data, a first prediction associated with a first state of the environment, the first prediction comprising a first state of an object in the environment at a future time;
determining, based at least in part on the first prediction and the route data, a second candidate action for controlling motion of the vehicle;
determining a second cost associated with the second candidate action, the second cost based at least in part on an upper bound cost, the upper bound cost being an estimate of a cost to execute a default action;
alternately applying one of the lower bound cost and the upper bound cost to one or more subsequent candidate actions; and
controlling the vehicle based at least in part on:
a path that comprises the first candidate action and the second candidate action; and
determining that a first total cost comprising the first cost and the second cost is less than a threshold or less than a second total cost associated with a second path comprising at least one candidate action that is different from at least one of the first candidate action or the second candidate action.