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:
Oct. 26, 2021

Filed:

Mar. 25, 2019
Applicant:

GM Global Technology Operations Llc, Detroit, MI (US);

Inventors:

Lawrence A. Bush, Shelby Township, MI (US);

Manpreet S. Bajwa, Windsor, CA;

Shuqing Zeng, Sterling Heights, MI (US);

Rickie A. Sprague, Commerce Township, MI (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 30/09 (2012.01); B60W 30/095 (2012.01); G05D 1/02 (2020.01); G06N 20/00 (2019.01); G01S 13/931 (2020.01);
U.S. Cl.
CPC ...
B60W 30/09 (2013.01); B60W 30/0956 (2013.01); G01S 13/931 (2013.01); G05D 1/0221 (2013.01); G06N 20/00 (2019.01); G05D 2201/0213 (2013.01);
Abstract

A risk maneuver assessment system and method to generate a perception of an environment of a vehicle and a behavior decision making model for the vehicle; a sensor system configured to provide the sensor input in the environment for filtering target objects; one or more modules configured to map and track target objects to make a candidate detection from multiple candidate detections of a true candidate detection as the tracked target object; apply a Markov Random Field (MRF) algorithm for recognizing a current situation of the vehicle and predict a risk of executing a planned vehicle maneuver at the true detection of the dynamically tracked target; apply mapping functions to sensed data of the environment for configuring a machine learning model of decision making behavior of the vehicle; and apply adaptive threshold to cells of an occupancy grid for representing an area of tracking of objects within the vehicle environment.


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