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
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However, these correlations have not been adequately or s...

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  • 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

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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...

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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...

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Application Information

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IPC IPC(8): G08G1/01
CPCG08G1/0125
Inventor 施云惠汪洋张勇尹宝才
Owner BEIJING UNIV OF TECH
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