Traffic speed prediction method and system and storage medium

A speed prediction and traffic technology, applied in prediction, control of traffic signals, neural learning methods, etc., can solve the problems of incomplete spatial feature mining of traffic speed data, large complexity of prediction models, slow convergence, etc., and achieve rich new map information. And effective, reduce the computational complexity, the effect of reducing the computational complexity

Pending Publication Date: 2020-09-01
HUNAN UNIV
View PDF5 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing graph convolutional neural network model does not fully mine the spatial characteristics of traffic speed data when predicting traffic speed. Most of them only consider the single spatial relationship of adjacent road sections or adjacent areas. There are many kinds of relationships. For exa

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Traffic speed prediction method and system and storage medium
  • Traffic speed prediction method and system and storage medium
  • Traffic speed prediction method and system and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0071] The embodiment of the present invention uses a multi-view graph convolutional neural network model to predict traffic speed, which is divided into five parts. The first part is data preprocessing and graph construction, the second part is graph fusion, and the third part builds a prediction model. The fourth part is to train the prediction model, and the fifth part is to test the experimental effect.

[0072] The first step, data preprocessing, includes two aspects, one is to preprocess the original traffic speed data, and the other is to generate different spatial relationship diagrams.

[0073] 1. The original traffic speed dataset. The original collection of traffic speed data usually does not meet the requirements, and can only meet our needs after processing. The first step of processing is to normalize the data, and the second step is to construct a training set and a test set.

[0074] The purpose of normalization is to alleviate the problem that the neural net...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a traffic speed prediction method and system and a storage medium, and the method comprises the steps: collecting an original traffic speed data set, dividing the data set intoa training set and a test set, mining different spatial relations of the original traffic speed data set, and constructing two road network graphs; fusing the adjacent matrixes of the two road network graphs into a new graph adjacent matrix; taking the training set and the new graph adjacency matrix as input of a traffic prediction model, and training to obtain a prediction model; and predictingthe traffic speed by using the prediction model. The spatial relationship can be fully and comprehensively mined, the complexity of model processing is reduced, and the traffic speed is accurately predicted.

Description

technical field [0001] The invention relates to the field of traffic data processing, in particular to a traffic speed prediction method, system and storage medium. Background technique [0002] In recent years, with the rapid development of intelligent transportation systems and various positioning technologies such as Global Positioning System (GPS), mobile devices, etc., the availability of traffic data is increasing. Mining valuable knowledge from traffic data is crucial to many real-world applications, including smart transportation, urban planning, public safety, etc. Traffic prediction is of great significance to the realization of traffic guidance, travel planning and congestion control. So how to make real-time and accurate traffic forecast has become more and more concerned. [0003] The traffic forecasting problem is defined as predicting the traffic information of a certain time period in the future based on the historical traffic information in the road networ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06Q10/04G06Q50/30G06N3/04G06N3/08G08G1/08
CPCG06Q10/04G06Q50/30G06N3/049G06N3/084G08G1/08G06N3/045
Inventor 张大方左若梁谢鲲
Owner HUNAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap