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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.

Patent No.:

US 11417216 B1

PDFFull Text
Date of Patent:
Aug. 16, 2022

Filed:

Mar. 11, 2020

Predicting a behavior of a road used using one or more coarse contextual information

Applicant:

Cartica Ai Ltd., Tel Aviv, IL;

Inventor:

Omer Jackobson, Tel-Aviv, IL;

Assignee:

AUTOBRAINS TECHNOLOGIES LTD., Tel-Aviv-Yafo, IL;

Attorney:

Reches Patents

Primary Examiner:

Dov Popovici

Int. Cl.
CPC ...
G08G 1/16 (2006.01); G06N 20/00 (2019.01); G08G 1/04 (2006.01); G06N 5/04 (2006.01); G06V 10/70 (2022.01); G06V 20/58 (2022.01); G06V 30/194 (2022.01); G06V 40/20 (2022.01); B60W 60/00 (2020.01); B60W 30/095 (2012.01); B60W 40/04 (2006.01);
U.S. Cl.
CPC ...
G08G 1/167 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06V 10/768 (2022.01); G06V 20/58 (2022.01); G06V 30/194 (2022.01); G06V 40/20 (2022.01); G08G 1/04 (2013.01); G08G 1/16 (2013.01); B60W 30/0956 (2013.01); B60W 40/04 (2013.01); B60W 60/0017 (2020.02); B60W 60/0027 (2020.02);
Abstract

A method for predicting behaviors of road users, the method may include sensing a vicinity of a vehicle to provide sensed information; processing the sensed information to provide compact contextual signatures of sensed road users within the vicinity of the vehicle; wherein a compact contextual signature of each a sensed road user includes (a) coarse contextual metadata regarding the sensed road user, (b) coarse location information regarding the sensed road user, (c) identifiers of other sensed road users, and (d) coarse situation information; feeding the compact contextual signatures to a machine learning process trained to estimate behaviors of road users based on compact contextual signatures of road users; and predicting, by the machine learning process, the behaviors of the sensed road users.

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