Short-term traffic flow prediction method based on convolutional neural network

Abstract

The invention provides a short-term traffic flow prediction method based on a convolutional neural network. The short-term traffic flow prediction method comprises the steps that firstly, the formats of input matrixes are determined according to the number of upstream and downstream road sections and the number of historical flow data predicted to be used; secondly, a structure of a convolutional neural network prediction model is determined according to the formats of input matrixes, and model training is completed by using the historical flow data of predicted road sections and the upstream and downstream road sections of the predicted road sections; finally, prediction is performed by using the trained model. The method utilizes the convolutional neural network having powerful characteristic learning capability to accurately predict short-term traffic flow, considers the flows of the predicted road sections and the upstream and downstream road sections of the predicted road sections simultaneously, and enables input data to be expanded to two dimensions so as to conform to the input format of the convolutional neural network. In addition, information of the road sections relevant with the predicted road sections is also provided to enable the prediction model to learn more flow characteristics, and accordingly the prediction accuracy is improved.

Description

technical field [0001] The present invention relates to a short-term traffic flow forecasting method. By using the convolutional neural network model in deep learning technology, combined with the traffic information of predicted road sections and related road sections, accurate short-term traffic flow forecasting is performed, which belongs to deep learning and intelligence. Cross-technical application areas of transportation systems. Background technique [0002] Intelligent Transportation System (ITS) is a real-time, accurate and efficient intelligent transportation network management system, which effectively integrates advanced information technology, communication technology, sensor technology, control technology and computer technology, and is an all-round solution to traffic problems. Congestion and an effective means to ensure the safety of traffic network transportation. A large number of applied research results at home and abroad show that ITS has shown great ad...

AI Technical Summary

Problems solved by technology

[0008] Technical problem: The purpose of this invention is to provide a short-term traffic flow prediction method based on convolutional neural network. This method firstly applies convolutional neural network to short-term traffic flow prediction, and uses the prediction road section and its upstream and downstream road sections Historical traffic data as input, using the excellent feature learning ability of convolutional neural network to fully obtain the hidden laws of traffic data, to a certain extent solve the problem of low prediction accuracy of existing neural network-based methods, and also provide A new idea of ​​short-term traffic forecasting

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