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:
Oct. 18, 2022

Filed:

Apr. 05, 2019
Applicant:

Toyota Research Institute, Inc., Los Altos, CA (US);

Inventors:

Avinash Balachandran, Sunnyvale, CA (US);

Carrie Bobier-Tiu, Sunnyvale, CA (US);

Assignee:

Toyota Research Institute, Inc., Los Altos, CA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/02 (2020.01); G06K 9/00 (2006.01); G05D 1/00 (2006.01); B60W 50/00 (2006.01); B60W 50/02 (2012.01); B60W 50/029 (2012.01); G07C 5/08 (2006.01); G06V 20/58 (2022.01); G06V 20/56 (2022.01); B60W 50/14 (2020.01);
U.S. Cl.
CPC ...
G05D 1/0238 (2013.01); B60W 50/0097 (2013.01); B60W 50/0205 (2013.01); B60W 50/029 (2013.01); B60W 50/14 (2013.01); G05D 1/0055 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); G06V 20/58 (2022.01); G06V 20/588 (2022.01); G07C 5/0808 (2013.01); B60W 2050/0083 (2013.01); B60W 2050/021 (2013.01); B60W 2050/0215 (2013.01); B60W 2050/146 (2013.01); G05D 1/0231 (2013.01); G05D 1/0255 (2013.01); G05D 1/0257 (2013.01); G05D 2201/0213 (2013.01);
Abstract

System, methods, and other embodiments described herein relate to improving the prediction efficiency of autonomous/semi-autonomous vehicles. In one embodiment, the system generates a provisional prediction according to sensor data from at least one sensor of a subject vehicle. The prediction can be associated with an aspect relating to operating the subject vehicle along a path. The system analyzes the provisional prediction in relation to a subsequent prediction about the aspect to determine a correspondence between the provisional prediction and the subsequent prediction. In response to determining that the correspondence satisfies an inaccuracy threshold, the system can store the provisional prediction and the sensor data associated with the provisional prediction to log potential inaccuracies in generating predictions based, at least in part, on the sensor data.


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