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Traffic jam prediction method and system

A prediction method and traffic congestion technology, applied in traffic control systems, traffic control systems of road vehicles, traffic flow detection, etc., can solve problems such as inaccurate traffic congestion prediction results, failure to consider the influence of road sections and time-space characteristics, etc., to achieve improved The effect of predicting the situation

Pending Publication Date: 2021-07-23
CHANGCHUN UNIV OF SCI & TECH
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Problems solved by technology

[0003] The above existing technologies do not take into account the influence of road sections and the spatio-temporal characteristics, resulting in inaccurate prediction results of traffic congestion

Method used

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  • Traffic jam prediction method and system
  • Traffic jam prediction method and system

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Embodiment Construction

[0066] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0067] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0068] Such as figure 1 with figure 2 As shown, the present embodiment provides a traffic jam prediction method, the method comprising:

[0069] Step 101: Obtain historical trajectory data of all vehicles in th...

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Abstract

The invention relates to a traffic jam prediction method and system. The method comprises the following steps: acquiring historical trajectory data of all vehicles in a road network to be predicted, wherein the to-be-predicted road network is composed of a plurality of road sections; for any road section, obtaining the average speed of the road section in a set time period according to the historical trajectory data of all the vehicles in the set time period of the road section; determining the average speed of each road section in all time periods as a congestion feature matrix of the road network to be predicted; obtaining an adjacent matrix of the to-be-predicted road network according to the position relation of all the road sections in the to-be-predicted road network; and inputting the congestion feature matrix of the road network to be predicted and the adjacent matrix of the road network to be predicted into a congestion prediction model to obtain a congestion prediction result. According to the invention, the prediction condition of traffic jam can be improved.

Description

technical field [0001] The invention relates to the technical field of traffic jam prediction, in particular to a traffic jam prediction method and system. Background technique [0002] In view of the complexity of the urban traffic network, with the maturity of deep learning technology, there are the following existing technologies to predict traffic congestion: (1) predict the node flow and edge flow of the entire road network through the multi-task learning model MDL, Get traffic jam situation. (2) Based on sparse trajectory data, a graph-based CNN-LSTM model is proposed for long-term traffic prediction. (3) Using graph convolution and temporal features, a time-dependent data reduction method is proposed for short-term traffic prediction. (4) Based on the deep convolutional neural network, a new method named PCNN is established for short-term traffic congestion prediction. [0003] The aforementioned prior art does not take into account the mutual influence of road sec...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06N3/08G06N3/04
CPCG08G1/0133G08G1/0129G06N3/08G06N3/044G06N3/045
Inventor 李松江赵健宏杨迪王鹏任志鹏宋小龙
Owner CHANGCHUN UNIV OF SCI & TECH
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