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. 31, 2022

Filed:

Aug. 31, 2018
Applicant:

Guangzhou Automobile Group Co., Ltd., Guangdong, CN;

Inventors:

Jun Gu, Guangdong, CN;

Qinggui Pan, Guangdong, CN;

Qiaojun He, Guangdong, CN;

Lulong Cai, Guangdong, CN;

Ming Fan, Guangdong, CN;

Qian Mao, Guangdong, CN;

Yanlin Li, Guangdong, CN;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G08G 1/052 (2006.01); H04W 4/46 (2018.01); G06N 20/00 (2019.01); G08G 1/0967 (2006.01); G08G 1/16 (2006.01); H04L 12/40 (2006.01);
U.S. Cl.
CPC ...
G08G 1/052 (2013.01); G06N 20/00 (2019.01); G08G 1/096725 (2013.01); G08G 1/161 (2013.01); G08G 1/166 (2013.01); H04L 12/40 (2013.01); H04W 4/46 (2018.02); H04L 2012/40215 (2013.01); H04L 2012/40273 (2013.01);
Abstract

An intersection traffic control method, apparatus and system are provided. The method includes that: a vehicle signal of a first vehicle at an intersection and a vehicle signal of a second vehicle located in a set zone in proximity to the intersection are acquired; the vehicle signal of the first vehicle and the vehicle signal of the second vehicle are input into an instruction learning model trained in advance based on a reinforcement learning principle, and a score of a preset traffic indicator of the first vehicle after executing a respective candidate action instruction is calculated; a reward of the first vehicle when executing the respective candidate action instruction is acquired according to the score of the preset traffic indicator, a candidate action instruction corresponding to a maximum reward is determined as an output result of the instruction learning model, and a next action instruction is determined according to the output result; and navigation of the first vehicle through the intersection is controlled according to the next action instruction.


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