A hadoop-based vehicle congestion acquisition method

An acquisition method and technology of congestion degree, applied in the field of Internet of Vehicles communication, can solve the problems of unsuitable analysis of traffic conditions, large amount of traffic information, and long time consumption, and achieve the effect of fast processing speed, improved computing efficiency, and less time.

Inactive Publication Date: 2017-05-24
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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Problems solved by technology

[0024] However, the mobile clustering algorithm is implemented in a serial manner. Firstly, the statistical GPS information is time- and regionalized through the MapReduce() function, and the GPS information at the same time t is divided into several regions, and then the calculations in each region are performed separately. After calculating the statistical congestion degree and linear congestion degree of an area, calculate the next area until all the areas at time t are calculated, and then calculate the statistical congestion degree and linear congestion degree at time t+1, press The time-growth sequence is calculated sequentially. This method uses sensor object technology to dynamically obtain information such as vehicle identification, position, instantaneous speed, forward direction, and real-time time. With the increase of traffic data acquisition sources, the amount of real-time traffic information is huge. It takes a long time and is inefficient to calculate, and it is not suitable for analyzing traffic conditions in the actual environment

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  • A hadoop-based vehicle congestion acquisition method
  • A hadoop-based vehicle congestion acquisition method
  • A hadoop-based vehicle congestion acquisition method

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[0055] figure 1 It is a flow chart of the Hadoop-based vehicle congestion degree acquisition method of the present invention.

[0056] In this example, if figure 1 Shown, the vehicle congestion degree acquisition method based on Hadoop of the present invention may further comprise the steps:

[0057] S101. Process statistical data through the MapReduce programming model; input the statistical GPS information, and divide the GPS information into N data fragments through the MapReduce programming model. When the Map() function reads the data fragments, one record is read each time, that is, the data fragments A row of GPS messages, read the next record after reading one record, the Map() function will decompose the read row of records into key-value pairs n ,V n >,n=1,2,…N, at K n Enter the offset of the first character of this line in the file, in V n Enter the content of this line of messages, where, V n The contents of the input message include: vehicle number no, gps me...

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Abstract

The invention discloses a Hadoop-based vehicle congestion degree acquisition method, which processes statistical GPS messages in parallel through multiple MapReduce tasks, and then calculates the statistical congestion degree and linear congestion degree of each area at the same time in parallel through a congestion degree calculation function In this way, it overcomes the defect of long computing time of the mobile cluster algorithm and greatly improves the computing efficiency. The Hadoop-based algorithm can automatically save data copies and expand computer clusters, and has high scalability and fault tolerance.

Description

technical field [0001] The invention belongs to the technical field of Internet of Vehicles communication, and more specifically, relates to a Hadoop-based method for acquiring vehicle congestion. Background technique [0002] Identifying hotspots of moving vehicles in urban areas is essential for many smart city applications, while vehicle hotspots can be described as areas with high vehicle congestion, and extremely high congestion hotspots are usually locations of traffic congestion. [0003] Intuitively, the congestion degree of a point reflects how crowded a point is. Measuring the congestion degree becomes difficult when the distribution of the vehicle set is unknown. To quantify the congestion degree of an unknown object set in a place, we propose the mobile cluster algorithm. [0004] We assume that there is a set of N vehicles deployed on a two-dimensional city plane A, among these N vehicles, a small subset is the set of sensors that we have full awareness of....

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G06F19/00
Inventor 廖丹卜思桐孙罡陆川虞红芳许都
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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