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. 02, 2026

Filed:

Sep. 11, 2024
Applicants:

Hyundai Motor Company, Seoul, KR;

Kia Corporation, Seoul, KR;

Inventors:

Eun Ji Jun, Hwaseong-si, KR;

Byeong Wook Jeon, Hwaseong-si, KR;

Dong Hoon Jeong, Hwaseong-si, KR;

Ki Sang Kim, Hwaseong-si, KR;

Assignees:

HYUNDAI MOTOR COMPANY, Seoul, KR;

KIA CORPORATION, Seoul, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B60W 30/14 (2006.01); B60W 50/06 (2006.01); B60W 50/10 (2012.01); B60W 60/00 (2020.01); G06N 3/0455 (2023.01);
U.S. Cl.
CPC ...
B60W 30/143 (2013.01); B60W 50/06 (2013.01); B60W 50/10 (2013.01); B60W 60/001 (2020.02); G06N 3/0455 (2023.01); B60W 2540/30 (2013.01);
Abstract

An autonomous driving control apparatus includes a memory and at least one processor. The at least one processor identifies first input information including at least one of a characteristic of a road, event information of the road, or any combination thereof and second input information including a characteristic of the vehicle. The at least one processor further performs cross-modal alignment of a backbone model for outputting a speed profile. The at least one processor also applies an output obtained by applying the first input information to a first encoder neural network, an output obtained by applying the second input information to a feature extraction neural network of the backbone model, and a target speed to a second decoder neural network. The at least one processor further obtains the speed profile from the second decoder neural network to perform main learning of the backbone model.


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