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. 14, 2024

Filed:

Feb. 18, 2021
Applicant:

Nvidia Corporation, Santa Clara, CA (US);

Inventors:

David Nister, Bellevue, WA (US);

Yizhou Wang, San Jose, CA (US);

Julia Ng, San Jose, CA (US);

Rotem Aviv, San Diego, CA (US);

Seungho Lee, San Jose, CA (US);

Joshua John Bialkowski, San Mateo, CA (US);

Hon Leung Lee, Bellevue, WA (US);

Hermes Lanker, Zürich, CH;

Raul Correal Tezanos, Santa Clara, CA (US);

Zhenyi Zhang, San Jose, CA (US);

Nikolai Smolyanskiy, Seattle, WA (US);

Alexey Kamenev, Carlsbad, CA (US);

Ollin Boer Bohan, Redmond, WA (US);

Anton Vorontsov, San Jose, CA (US);

Miguel Sainz Serra, Palo Alto, CA (US);

Birgit Henke, Seattle, WA (US);

Assignee:

NVIDIA Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 60/00 (2020.01); B60W 50/00 (2006.01); G05D 1/00 (2006.01); G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
B60W 60/0011 (2020.02); B60W 50/0097 (2013.01); G05D 1/0212 (2013.01); G06N 3/08 (2013.01);
Abstract

Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.


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