Traffic flow prediction method and device based on deep learning

A technology for traffic flow and flow prediction, which is applied in traffic flow detection, neural learning methods, and traffic control systems for road vehicles. It can solve the problem of low prediction accuracy and achieve the effect of improving accuracy.

Pending Publication Date: 2020-03-27
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Embodiments of the present invention provide a traffic flow prediction method and device based on deep learning, to at least solve the technical problem of low prediction accuracy of existing traffic flow prediction methods

Method used

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  • Traffic flow prediction method and device based on deep learning
  • Traffic flow prediction method and device based on deep learning
  • Traffic flow prediction method and device based on deep learning

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Embodiment 1

[0065] According to an embodiment of the present invention, a traffic flow prediction method based on deep learning is provided, see figure 1 , including the following steps:

[0066] S1: Receive a traffic prediction request sent by a user terminal, where the traffic prediction request at least carries a target node identifier.

[0067] In this embodiment, the user terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices; the traffic forecast request is generated according to the information selected or input by the user terminal; the target node identification It is used to identify the target node, which can be letters, numbers, etc., and is not specifically limited here.

[0068] Specifically, when a traffic prediction request sent by a user terminal according to actual application requirements is received, the target node identifier carried in the traffic prediction request can be ob...

Embodiment 2

[0141] According to another embodiment of the present invention, a kind of traffic flow prediction device based on deep learning is provided, see Figure 6 ,include:

[0142] A request receiving module 601, configured to receive a traffic forecast request sent by a user terminal, where the traffic forecast request at least carries a target node identifier;

[0143] In this embodiment, the user terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices; the traffic forecast request is generated according to the information selected or input by the user terminal; the target node identification It is used to identify the target node, which can be letters, numbers, etc., and is not specifically limited here.

[0144] Specifically, when a traffic prediction request sent by a user terminal according to actual application requirements is received, the target node identifier carried in the traffic...

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Abstract

The invention relates to the field of spatio-temporal data mining or intelligent traffic, in particular to a traffic flow prediction method and device based on deep learning. The traffic flow prediction method comprises the following steps: receiving a flow prediction request sent by a user terminal; then, responding to the flow prediction request, and obtaining traffic flow information of a target road network corresponding to the target node identifier; acquiring spatiotemporal feature information based on the traffic flow information; and inputting the space-time feature information into aspace-time diagram convolution model to perform model prediction operation, and obtaining a flow prediction result, so that the influence of the spatial-temporal characteristics of the traffic flow ofthe whole road network on the traffic flow of the target node can be more comprehensively considered from the perspective of spatial-temporal correlation. The traffic flow prediction method and device based on deep learning can improve the accuracy of predicting the traffic flow of the road network.

Description

technical field [0001] The present invention relates to the field of spatio-temporal data mining or intelligent transportation, in particular, to a traffic flow prediction method and device based on deep learning. Background technique [0002] The interconnection in the field of transportation is the basis for realizing the interconnection of people flow, logistics, information flow and capital flow in urban agglomerations. A smooth road network in the metropolitan area is the most important thing in the infrastructure construction of the metropolitan area. The problem of traffic flow forecasting is crucial to constructing an intelligent highway network. In order to improve the operational capacity of the road network, improve people's travel efficiency, and reduce road traffic accidents, it is necessary to accurately predict the road traffic flow in advance and guide the traffic flow accordingly. [0003] On the other hand, with the construction and use of a large number ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/04G06N3/08G08G1/01
CPCG06Q10/04G06N3/08G08G1/0125G06N3/044G06N3/045
Inventor 叶洁瑕赵娟娟须成忠叶可江
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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