Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Completion method of road network traffic data based on adaptive space-time constraint low-order algorithm

A traffic data, spatiotemporal data technology, applied in the field of image processing and intelligent transportation, can solve the problem of insufficient correlation or take into account at the same time, and achieve the effect of improving accuracy

Active Publication Date: 2018-05-08
BEIJING UNIV OF TECH
View PDF4 Cites 34 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these correlations have not been adequately or simultaneously taken into account in previous imputation methods

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
  • Completion method of road network traffic data based on adaptive space-time constraint low-order algorithm
  • Completion method of road network traffic data based on adaptive space-time constraint low-order algorithm
  • Completion method of road network traffic data based on adaptive space-time constraint low-order algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] Through the analysis of the traffic data matrix, it is found that it not only has the characteristics of global low rank, but also has strong time and space characteristics. Therefore, while introducing the low rank algorithm, factorize the original matrix, and according to its time dimension and space Dimensional features introduce spatio-temporal constraints.

[0023] Such as figure 1 As shown, this method of complementing road network traffic data based on the adaptive spatio-temporal constraint low-rank algorithm includes the following steps:

[0024] (1) Construct the spatio-temporal data matrix of road network traffic data;

[0025] (2) Perform factor matrix decomposition on the spatio-temporal data matrix, and introduce an unconstrained low-rank restoration method;

[0026] (3) Add the time-series variation characteristics and spatial similarity characteristics of traffic data as space-time constraint items to more accurately complete the missing points.

[00...

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 present invention discloses a completion method of road network traffic data based on an adaptive space-time constraint low-order algorithm. The accuracy of the completed data is greatly improvedwhen a data loss rate is large, and the completion method provided by the invention has a good application effect on traffic data restoration in different time-space loss modes. The method comprises the steps of: (1) constructing a time-space data matrix of road network traffic data; (2) performing factor matrix decomposition of the time-space data matrix, and introducing a non-constraint low-order restoration method; and (3) adding time sequence change features and space similar features of the traffic data as time-space constraint terms to more accurately complete missing points.

Description

technical field [0001] The invention belongs to the technical field of image processing and intelligent transportation, and in particular relates to a method for complementing road network traffic data based on an adaptive spatiotemporal constraint low-rank algorithm. Background technique [0002] Traffic status information is very important for travelers and traffic monitoring centers, especially in avoiding and alleviating traffic congestion. By knowing the traffic status information, travelers can optimize their own travel routes and shorten travel time, and the traffic monitoring center can provide effective traffic guidance to travelers. At the same time, the emergence of multimedia services and Internet-friendly portable devices has greatly promoted the continuous development of transportation networks, such as induction loop detectors, microwave detectors, video surveillance cameras, and GPS floating vehicles. General static detectors such as underground induction co...

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): G08G1/01
CPCG08G1/0125
Inventor 施云惠汪洋张勇尹宝才
Owner BEIJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com