US 12,091,042 B2
Method and system for training an autonomous vehicle motion planning model
Christopher Cunningham, Pittsburgh, PA (US); and Maria Jahja, Pittsburgh, PA (US)
Assigned to Ford Global Technologies, LLC, Dearborn, MI (US)
Filed by FORD GLOBAL TECHNOLOGIES, LLC, Dearborn, MI (US)
Filed on Aug. 2, 2021, as Appl. No. 17/391,099.
Prior Publication US 2023/0037071 A1, Feb. 2, 2023
Int. Cl. B60W 60/00 (2020.01); B60W 50/14 (2020.01); G01C 21/34 (2006.01); G06N 20/00 (2019.01)
CPC B60W 60/001 (2020.02) [B60W 50/14 (2013.01); G01C 21/3453 (2013.01); G06N 20/00 (2019.01); B60W 2050/146 (2013.01); B60W 2420/403 (2013.01); B60W 2420/408 (2024.01)] 17 Claims
OG exemplary drawing
 
1. A computer-implemented method of training an autonomous vehicle motion planning model, the method comprising:
receiving a data log comprising data representing one or more objects detected by an autonomous vehicle (AV) over a time period;
identifying a group of sample times in the data log, in which each of the sample times represents a time at which a motion planning system of the AV made a choice in response to a state of one or more of the objects;
for each of the sample times, generating a plurality of candidate trajectories for the AV;
outputting the plurality of candidate trajectories on a display device;
receiving, via a user interface, a label for each of the candidate trajectories, wherein the label for each candidate trajectory includes a rating for that candidate trajectory;
saving, to a data set, each of the candidate trajectories in association with its label and the data from the log for its corresponding sample time;
applying the data set to an AV motion planning model to train the AV motion planning model;
in response to receiving, via the user interface, a request to play the data log, causing the display device to play a scene that includes the AV moving along a route and one or more of actors;
pausing the scene at one of the sample times and outputting the plurality of candidate trajectories while the pausing occurs; and
resuming the scene after receiving the labels for the plurality of candidate trajectories.