A Traffic Status Detection Method Based on Multivariate Data Fusion

Abstract

The invention discloses a traffic state detecting method based on multi-data fusion. On the basis of a clustering algorithm, GPS track segmentation is carried out on taxi GPS data and mobile phone GPSdata respectively based on users to obtain all taxi GPS segmentation tracks and mobile phone GPS segmentation tracks; with the taxi GPS segmentation tracks as training samples, an identification model is constructed and similar taxi GPS segmentation tracks are extracted in the mobile phone GPS segmentation tracks; on the basis of a map matching algorithm, the taxi GPS segmentation tracks and thesimilar taxi GPS segmentation tracks are matched to road sections in an urban road network; with a matching result of the two kinds of tracks, vehicle driving speeds at the corresponding road sectionsare calculated respectively; and according to an evidence theory, the vehicle driving speeds, calculated respectively based on the matching result of the two kinds of tracks, of the road section arefused and the vehicle driving speed of the road section is estimated. Therefore, the urban road traffic state information is detected accurately.

Description

technical field [0001] The invention belongs to the technical field of traffic, and in particular relates to a traffic state detection method based on multivariate data fusion. Background technique [0002] With the continuous development of urbanization in our country, urban roads are becoming more and more complex, and the management and control of urban traffic by administrative departments is also becoming more and more difficult. Therefore, real-time detection and extensive and accurate evaluation of urban road traffic conditions are of great significance. Traditional traffic condition detection is mainly based on manual traffic survey and manual vehicle speed measurement on road sections. In recent years, with the rapid development of sensing technology and communication technology, traffic condition information recorded by various traffic sensing devices has been widely used It is applied to research on traffic management and control, such as loop detector data record...

AI Technical Summary

Problems solved by technology

[0003] 1) Although taxi GPS data can effectively record the location information of taxis, taxis tend to drive on urban arterial roads, and the coverage of taxis in lower-level urban roads and suburban areas is still low. Comprehensive detection of conditions has certain limitations

At the same time, its recording frequency is low, and there are certain limitations on the accuracy of the detected traffic conditions.

[0004] 2) Mobile phone GPS data records traffic user information including various modes of transportation, including buses, taxis, private cars, bicycles, pedestrians, etc., and the research on urban traffic conditions is mainly for buses, taxis, etc. Motor vehicles, bicycles, pedestrians and other information recorded by mobile phone GPS data will cause serious interference and influence on the traffic condition detection results

[0005] 3) There may be inconsistencies or even contradictions in the traffic status sensed by the two GPS data, and a method is needed to measure this inconsistency, so as to fuse on this basis to obtain an accurate traffic status

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