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:
Jul. 19, 2022

Filed:

Mar. 04, 2020
Applicant:

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

Inventors:

Netalee Efrat Sela, Herzliya, IL;

Max Bluvstein, Herzliya, IL;

Bat El Shlomo, Hod Hasharon, IL;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 40/06 (2012.01); G08G 1/16 (2006.01); G06K 9/62 (2022.01); B60W 50/00 (2006.01); B60W 60/00 (2020.01); G06V 20/56 (2022.01); G05D 1/00 (2006.01);
U.S. Cl.
CPC ...
B60W 40/06 (2013.01); B60W 50/0097 (2013.01); B60W 60/001 (2020.02); G06K 9/6256 (2013.01); G06K 9/6262 (2013.01); G06V 20/588 (2022.01); G08G 1/167 (2013.01); B60W 2420/42 (2013.01); B60W 2420/52 (2013.01); B60W 2552/53 (2020.02); G05D 1/0088 (2013.01); G05D 2201/0213 (2013.01);
Abstract

A system for end to end prediction of lane detection uncertainty includes a sensor device of a host vehicle generating data related to a road surface and a navigation controller including a computerized processor operable to monitor an input image from the sensor device, utilize a convolutional neural network to analyze the input image and output a lane prediction and a lane uncertainty prediction, and generate a commanded navigation plot based upon the lane prediction and the lane uncertainty prediction. The convolutional neural network is initially trained using a per point association and error calculation, including associating a selected ground truth lane to a selected set of data points related to a predicted lane and then associating at least one point of the selected ground truth lane to a corresponding data point from the selected set of data points related to the predicted lane.


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