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:
Sep. 14, 2021

Filed:

Nov. 28, 2016
Applicant:

Toyota Jidosha Kabushiki Kaisha, Toyota, JP;

Inventors:

Oluwatobi Olabiyi, Mountain View, CA (US);

Eric Martinson, Sunnyvale, CA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 7/00 (2006.01); G06N 20/00 (2019.01); G06N 3/04 (2006.01); B60W 40/09 (2012.01); G01C 21/26 (2006.01); B60W 50/00 (2006.01); G01C 21/32 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06N 7/005 (2013.01); B60W 40/09 (2013.01); B60W 50/0097 (2013.01); G01C 21/26 (2013.01); G01C 21/32 (2013.01); G06N 3/0445 (2013.01); G06N 3/084 (2013.01); G06N 20/00 (2019.01); B60W 2050/0029 (2013.01); B60W 2420/42 (2013.01); B60W 2420/52 (2013.01); B60W 2420/54 (2013.01); B60W 2556/55 (2020.02); B60W 2556/65 (2020.02);
Abstract

By way of example, the technology disclosed by this document may be implemented in a method that includes receiving stored sensor data describing characteristics of a vehicle in motion at a past time and extracting features for prediction and features for recognition from the stored sensor data. The features for prediction may be input into a prediction network, which may generate a predicted label for a past driver action based on the features for prediction. The features for recognition may be input into a recognition network, which may generate a recognized label for the past driver action based on the features for recognition. In some instances, the method may include training prediction network weights of the prediction network using the recognized label and the predicted label.


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