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:
May. 07, 2024

Filed:

Jul. 28, 2021
Applicant:

Uatc, Llc, Mountain View, CA (US);

Inventors:

Yiming Gu, Pittsburgh, PA (US);

Galen Clark Haynes, Pittsburgh, PA (US);

Anh Tuan Hoang, Jersey City, NY (US);

Sumit Kumar, Sunnyvale, CA (US);

Micol Marchetti-Bowick, Pittsburgh, PA (US);

Assignee:

UATC, LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/04 (2023.01); B60W 50/00 (2006.01);
U.S. Cl.
CPC ...
B60W 50/0097 (2013.01); G06N 3/04 (2013.01); B60W 2050/0028 (2013.01); B60W 2554/4041 (2020.02); B60W 2554/4042 (2020.02); B60W 2554/4043 (2020.02); B60W 2554/801 (2020.02); B60W 2554/802 (2020.02);
Abstract

Systems and methods for predicting interactions between objects and predicting a trajectory of an object are presented herein. A system can obtain object data associated with a first object and a second object. The object data can have position data and velocity data for the first object and the second object. Additionally, the system can process the obtained object data to generate a hybrid graph using a graph generator. The hybrid graph can have a first node indicative of the first object and a second node indicative of the second object. Moreover, the system can process, using an interaction prediction model, the generated hybrid graph to predict an interaction type between the first node and the second node. Furthermore, the system can process, using a graph neural network model, the predicted interaction type between the first node and the second node to predict a trajectory of the first object.


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