US 11,934,962 B2
Object association for autonomous vehicles
Carlos Vallespi-Gonzalez, Pittsburgh, PA (US); Abhishek Sen, Pittsburgh, PA (US); and Shivam Gautam, Pittsburgh, PA (US)
Assigned to UATC, LLC, Mountain View, CA (US)
Filed by UATC, LLC, Mountain View, CA (US)
Filed on Apr. 10, 2023, as Appl. No. 18/297,937.
Application 18/297,937 is a continuation of application No. 17/494,165, filed on Oct. 5, 2021, granted, now 11,651,240.
Application 17/494,165 is a continuation of application No. 16/038,730, filed on Jul. 18, 2018, granted, now 11,138,745, issued on Oct. 5, 2021.
Claims priority of provisional application 62/664,678, filed on Apr. 30, 2018.
Prior Publication US 2023/0259792 A1, Aug. 17, 2023
Int. Cl. G06N 5/022 (2023.01); G06N 5/046 (2023.01); G06N 20/00 (2019.01); G06T 7/292 (2017.01); G06T 7/70 (2017.01); G06V 10/764 (2022.01); G06V 20/30 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01)
CPC G06N 5/022 (2013.01) [G06N 5/046 (2013.01); G06N 20/00 (2019.01); G06T 7/292 (2017.01); G06T 7/70 (2017.01); G06V 10/764 (2022.01); G06V 20/30 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); G06T 2207/10044 (2013.01); G06T 2207/10052 (2013.01); G06T 2207/30261 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for machine-learned model training, the method comprising:
inputting, into an object association model, training data indicative of a plurality of training objects and a plurality of training object tracks in an environment over a plurality of time intervals;
receiving, from the object association model, an output indicative of a training association of at least one training object at a most recent time interval of the plurality of time intervals and at least one training object track at a plurality of time intervals preceding the most recent time interval;
determining, for the object association model, a similarity score based on a comparison of the training association to a ground truth association, wherein the similarity score is positively correlated with greater accuracy of association by the object association model; and
adjusting at least one parameter of the object association model based on the similarity score.