Traffic signal control method and system based on reinforcement learning and graph attention network
A traffic signal and reinforcement learning technology, which is applied in the traffic control system of road vehicles, traffic control system, neural learning method, etc., can solve the problem of not being able to realize efficient sharing and collaborative control of signals between intersections
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[0109] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, several changes and improvements can be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.
[0110] The present invention can be applied to traffic signal control scenarios in the case of multiple traffic intersections;
[0111] According to the present invention, a traffic signal control method based on reinforcement learning and graph attention network includes:
[0112] Initialization steps: define various variables in the traffic signal control problem, and initialize the traffic signal algorithm model;
[0113] Observation information vectorization step: reduce the dimension of t...
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