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:
Jun. 25, 2024

Filed:

Mar. 18, 2021
Applicant:

Baidu Usa Llc, Sunnyvale, CA (US);

Inventors:

Liangliang Zhang, Sunnyvale, CA (US);

Dong Li, Sunnyvale, CA (US);

Jiangtao Hu, Sunnyvale, CA (US);

Jiaming Tao, Sunnyvale, CA (US);

Yifei Jiang, Sunnyvale, CA (US);

Assignee:

BAIDU USA LLC, Sunnyvale, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B60W 50/00 (2006.01); G01C 21/34 (2006.01); G05D 1/00 (2006.01); G06N 20/00 (2019.01); G06V 10/776 (2022.01); G06V 10/96 (2022.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
B60W 50/0097 (2013.01); G01C 21/3446 (2013.01); G05D 1/0088 (2013.01); G05D 1/0214 (2013.01); G05D 1/0221 (2013.01); G06N 20/00 (2019.01); G06V 10/776 (2022.01); G06V 10/96 (2022.01); G06V 20/58 (2022.01);
Abstract

A sensor aggregation framework for autonomous driving vehicles is disclosed. In one embodiment, sensor data is collected from one or more sensors mounted on an autonomous driving vehicle (ADV) while the ADV is moving within a region of interest (ROI) that includes a number of obstacles. The sensor data includes obstacle information of the obstacles and vehicle data of the ADV. Each of the vehicle data is timestamped with a current time at which the vehicle data is captured to generate a number of timestamps that correspond to the vehicle data. The obstacle information, the vehicle data, and the corresponding timestamps are aggregated into training data. The training data is used to train a set of parameters that is subsequently utilized to predict at least in part future obstacle behaviors and vehicle movement of the ADV.


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