Traffic congestion propagation prediction method based on space-time diagram convolutional neural network

A convolutional neural network and propagation prediction technology, applied in the field of traffic congestion propagation prediction based on spatiotemporal graph convolutional neural network, can solve the problems of poor prediction performance of congestion propagation model, complex traffic network, poor performance of prediction model, etc. , to achieve the effect of preventing and clearing traffic congestion

Active Publication Date: 2021-02-26
东北大学秦皇岛分校
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Problems solved by technology

XL.Ma and others built a deep convolutional neural network to predict short-term traffic flow speed, but it is difficult to accurately capture traffic information in the time domain
YP.Liu et al. proposed a convolutional long-short-term memory network to simultaneously capture the spatio-temporal characteristics of traffic speed to predict road traffic speed, but this model can only extract grid-type traffic data
However, th...

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  • Traffic congestion propagation prediction method based on space-time diagram convolutional neural network
  • Traffic congestion propagation prediction method based on space-time diagram convolutional neural network
  • Traffic congestion propagation prediction method based on space-time diagram convolutional neural network

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[0050] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. The following examples are intended to illustrate the present invention, but not to limit the scope of the present invention.

[0051] A traffic congestion propagation prediction method based on spatiotemporal graph convolutional neural network, such as figure 1 shown, including the following steps:

[0052] Step 1: Obtain traffic data source data, and make traffic speed dataset and sensor network adjacency matrix data;

[0053] Step 1.1: Download a state performance evaluation system (PeMS) traffic data set from the Internet; the traffic data set includes the location information of the speed sensor on the traffic road network and the traffic speed data detected by the sensor; the traffic speed data is divided into training datasets and validation datasets;

[0054] In this embodiment, the selected location for the ...

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Abstract

The invention provides a traffic congestion propagation prediction method based on a space-time diagram convolutional neural network, and relates to the technical field of traffic big data mining andanalysis. Traffic data source data are acquired, a traffic speed data set and sensor network adjacent matrix data are made, a data driving mode is adopted, a space-time diagram convolutional neural network is introduced, and the traffic speed prediction precision of a target road section is improved. A speed prediction module is introduced into a congestion propagation model framework, so that thetraffic congestion prediction precision is improved, the traffic congestion propagation process is accurately represented, and the problems of low prediction precision, time-consuming algorithm operation and the like caused by poor spatial feature extraction of an existing traffic congestion propagation prediction scheme are solved; and the propagation condition of the congestion occurrence roadsection to the adjacent traffic road in the future time period is predicted.

Description

technical field [0001] The invention relates to the technical field of traffic big data mining and analysis, in particular to a traffic congestion propagation prediction method based on a spatiotemporal graph convolutional neural network. Background technique [0002] In today's society, many large cities regard traffic congestion as one of the problems that need to be solved urgently. When traffic congestion occurs in an area of ​​the traffic road network, this congested area will affect the traffic conditions of nearby roads, and even cause congestion on nearby sub-roads. Therefore, it is necessary to create an efficient model to predict the propagation of congestion in advance to predict when the adjacent road segments of the congestion source will be affected in the near future. In view of the above problems, the present invention proposes a traffic congestion propagation prediction method based on a spatiotemporal graph convolutional neural network, which has important...

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Application Information

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IPC IPC(8): G08G1/01G06Q10/04G06Q50/26G06N3/04G06N3/08
CPCG08G1/0104G08G1/0125G06Q10/04G06Q50/26G06N3/08G06N3/045
Inventor 郭戈刘金沅高振宇
Owner 东北大学秦皇岛分校
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