Road geometric feature extraction method based on taxi track data
A trajectory data and geometric feature technology, applied in the direction of electrical digital data processing, special data processing applications, traffic control systems of road vehicles, etc., can solve the problem of low refinement of road network information extraction, and achieve the process of trajectory point offset Simple, avoids the effects of mathematical operations
Inactive Publication Date: 2018-11-09
FUZHOU UNIV
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[0004] In view of this, the purpose of the present invention is to propose a road geometric feature extraction method based on taxi trajectory data, which solves the problem of low refinement of current road network information extraction, can reflect the real topological relationship of the road network, and realize road Extraction of driving direction information
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[0054] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0055] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0056] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinatio...
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The invention relates to a road geometric feature extraction method based on taxi track data. The method comprises the steps of firstly, preprocessing the taxi track data; secondly, calculating a driving direction angle of each track point; thirdly, traversing an original track point set to obtain a similarity track point set of track points Pi; fourthly, traversing the similarity track point set,and performing calculation to obtain offset distances of the track points Pi, thereby obtaining coordinates of the track points Pi after offset; and fifthly, finishing traversal of the track point set, updating the coordinates of the offset track points Pi into current coordinates of the track points, calculating an average value of the offset distances of all the track points, if the average value is smaller than or equal to a threshold value, converting the offset track points into track lines, making a buffer area for each track line, performing fusion into surface elements for performingbinarization, and extracting a road network L by utilizing an ArcScan tool. According to the method, the track points are offset, so that the situation that the tracks adjacent to different driving directions are gathered into one bundle is effectively avoided; the extracted road network can better reflect the real road structure; and the method has relatively high practical values.
Description
technical field [0001] The invention relates to the field of geographic information system and intelligent transportation research, in particular to a road geometric feature extraction method based on taxi track data. Background technique [0002] As a key component of basic geographic information data, urban road network data is an important data source for urban intelligent transportation construction. Accurate and fine road network data can provide effective decision-making support for urban traffic congestion control and urban planning. Highly detailed road network information is an important task in the current transportation field. With the maturity of mobile positioning technology, taxis equipped with GPS positioning devices can obtain a large amount of spatio-temporal data about urban road networks in a short period of time, which has the advantages of real-time, low cost, and strong pertinence. Refined road network information has become an important research conte...
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IPC IPC(8): G06F17/50G08G1/01
CPCG08G1/0125G06F30/20
Inventor 邬群勇吴祖飞张良盼
Owner FUZHOU UNIV