Short-term traffic flow control method based on graph convolution recurrent neural network
A cyclic neural network, short-term traffic flow technology, applied in road vehicle traffic control systems, traffic control systems, biological neural network models, etc. The time and space characteristics of the vehicle passing through the bayonet are not considered to achieve the effect of accurate prediction results
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[0024] In order to better illustrate the content of the present invention, the specific embodiments of the present invention will be further described below with reference to the accompanying drawings and embodiments of the present invention.
[0025] Such as figure 1 As shown, the present invention includes four modules: a data acquisition module, a road network topology building module, a model building module, and a prediction and analysis module.
[0026] The present invention is a short-term traffic flow control method based on graph convolutional recurrent neural network, such as figure 2 As shown, the specific steps of the method are:
[0027] S1: Extract vehicle information through roadside inspection equipment to obtain data sources;
[0028] S2: Construct a traffic flow sequence with a graph structure;
[0029] S3: According to the graph structure traffic flow sequence combined with the multi-level of the time dimension, the short-term component model of the spatiotemporal gr...
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