The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 12, 2024

Filed:

Jun. 30, 2021
Applicant:

Zoox, Inc., Foster City, CA (US);

Inventors:

Peter Scott Schleede, Foster City, CA (US);

Prateek Chandresh Shah, San Francisco, CA (US);

Assignee:

Zoox, Inc., Foster City, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 30/09 (2012.01); B60W 10/18 (2012.01); B60W 10/20 (2006.01); B60W 30/095 (2012.01); B60W 30/16 (2020.01); B60W 50/06 (2006.01); B60W 60/00 (2020.01); G06F 18/214 (2023.01); G06F 18/2431 (2023.01); G06N 20/00 (2019.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
B60W 30/09 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); B60W 30/0956 (2013.01); B60W 30/162 (2013.01); B60W 50/06 (2013.01); B60W 60/0013 (2020.02); B60W 60/0015 (2020.02); G06F 18/214 (2023.01); G06F 18/2431 (2023.01); G06N 20/00 (2019.01); G06V 20/56 (2022.01);
Abstract

Techniques for determining classifications associated with vehicle behavior by a machine learned model are discussed herein. A computing device can combine a variety of classifier labels as input to train a machine learned model to determine classifications that represent a vehicle behavior as either good behavior or bad behavior. The machine learned model may receive weak classifier labels that classify an aspect of a vehicle behavior as 'good,' “bad,” or “unknown” (relative to the classification) to generate training data for training the machine learning model. Data associated with a vehicle or simulated vehicle may be input to the trained machine learned model to classify good vehicle behavior or bad vehicle behavior even when the model has not been exposed to the precise scenarios represented in the training data.


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