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. 17, 2023

Filed:

Jul. 30, 2021
Applicant:

Lyft, Inc., San Francisco, CA (US);

Inventors:

Robert Earl Rasmusson, San Francisco, CA (US);

Taggart Matthiesen, Kentfield, CA (US);

Craig Dehner, San Francisco, CA (US);

Linda Dong, San Francisco, CA (US);

Frank Taehyun Yoo, San Carlos, CA (US);

Karina van Schaardenburg, San Francisco, CA (US);

John Tighe, San Francisco, CA (US);

Matt Vitelli, San Francisco, CA (US);

Jisi Guo, San Francisco, CA (US);

Eli Guerron, San Francisco, CA (US);

Assignee:

Lyft, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G05D 1/02 (2020.01); G05D 1/00 (2006.01); G06T 7/20 (2017.01); G06K 9/62 (2022.01); G01C 21/36 (2006.01); B62D 15/02 (2006.01); G06V 20/56 (2022.01); G06F 18/24 (2023.01);
U.S. Cl.
CPC ...
G01C 21/3638 (2013.01); B62D 15/0285 (2013.01); G01C 21/365 (2013.01); G05D 1/0044 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); G05D 1/0246 (2013.01); G05D 1/0274 (2013.01); G06F 18/24 (2023.01); G06T 7/20 (2013.01); G06V 20/56 (2022.01); B60W 2554/00 (2020.02); G05D 2201/0212 (2013.01); G05D 2201/0213 (2013.01); G06T 2207/30252 (2013.01); G06T 2207/30256 (2013.01); G06T 2207/30261 (2013.01);
Abstract

In one embodiment, a method includes receiving sensor data corresponding to an environment external of a vehicle. The sensor data include data points. The method includes determining one or more subsets of the data points. The method includes comparing the one or more subsets of the data points to one or more predetermined data patterns. Each of the one or more predetermined data patterns corresponds to an object classification. The method includes computing a confidence score for each subset of data points of the one or more subsets of the data points as corresponding to each of the one or more predetermined data patterns based on the comparison. The method includes generating a classification for an object in the environment external of the vehicle based on the confidence score.


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