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. 23, 2023

Filed:

Nov. 25, 2020
Applicants:

Toyota Research Institute, Inc., Los Altos, CA (US);

Massachusetts Institute of Technology, Cambridge, MA (US);

Inventors:

Xin Huang, Cambridge, MA (US);

Stephen G. McGill, Broomall, PA (US);

Jonathan A. DeCastro, Arlington, MA (US);

Brian C. Williams, Cambridge, MA (US);

Luke S. Fletcher, Cambridge, MA (US);

John J. Leonard, Newton, MA (US);

Guy Rosman, Newton, PA (US);

Assignees:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06V 20/58 (2022.01); G06V 10/82 (2022.01); G06V 20/52 (2022.01); B60W 60/00 (2020.01); G06V 20/40 (2022.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
B60W 60/0011 (2020.02); B60W 60/001 (2020.02); G06F 18/2148 (2023.01); G06N 3/08 (2013.01); G06V 10/82 (2022.01); G06V 20/41 (2022.01); G06V 20/52 (2022.01); G06V 20/58 (2022.01); B60W 2420/403 (2013.01);
Abstract

A system and method for generating a predicted vehicle trajectory includes a generative adversarial network configured to receive a trajectory vector of a target vehicle and generate a set of latent state vectors using the received trajectory vector and an artificial neural network. The latent state vectors each comprise a high-level sub-vector, Z. The GAN enforces Zto be correlated to an annotation coding representing semantic categories of vehicle trajectories. The GAN selects a subset, from the set of latent state vectors, using farthest point sampling and generates a predicted vehicle trajectory based on the selected subset of latent state vectors.


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