A method of vehicle trajectory clustering based on graph theory

A technology of vehicle trajectory and clustering method, which is applied in the field of vehicle trajectory clustering based on graph theory, and can solve problems such as things without any internal connection, unrecognizable, and difficult to cluster conclusions

Inactive Publication Date: 2018-12-18
FUZHOU UNIV
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Problems solved by technology

[0004] Traditional clustering methods such as DBscan and GMM algorithms have certain difficulties in obtaining clustering conclusions when the sample size is large
Since the relative coefficient is based on the internal structure of the data set to establish an index that reflects the internal relationship between the data, in pra

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  • A method of vehicle trajectory clustering based on graph theory
  • A method of vehicle trajectory clustering based on graph theory
  • A method of vehicle trajectory clustering based on graph theory

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0042] 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.

[0043] 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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Abstract

The invention relates to a vehicle trajectory clustering method based on graph theory. Firstly, the vehicle networking data is obtained, and the massive vehicle trajectory data is cleaned by using a Spark platform. Secondly, the coordinate points are projected onto the map, and the connected graph is formed according to the set K value and the relative approximation through the relative distance relation of the coordinate points, and then the clusters whose connectivity strength is greater than the preset value are merged by using the interconnectivity; finally, the real taxi trajectory data are analyzed to get the traffic flow of different time periods and different areas, that is, the optimal taxi-hailing scheme is given. The invention can effectively improve the speed and quality of data processing.

Description

technical field [0001] The invention relates to the field of vehicle networking and computing, in particular to a graph theory-based vehicle trajectory clustering method. Background technique [0002] With the rapid expansion of the scale of the application system in the vehicle industry, the data generated by the vehicle application is growing explosively, and the intelligent transportation system is facing huge challenges in data collection, processing, analysis, and utilization. In the context of the rapid development of information technology and cloud computing, the concept of Internet of Vehicles has gradually become familiar to people. As a typical application of the Internet of Things, the Internet of Vehicles makes it possible to finely collect the spatio-temporal information of vehicles running on the road network, thereby realizing more intelligent management of traffic. [0003] Cluster analysis method in data analysis technology is an effective method to study ...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2321G06F18/29
Inventor 冯心欣李剑斌柳泽烽郑海峰
Owner FUZHOU UNIV
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