Hadoop-based massive traffic data processing method

A traffic data and processing method technology, applied in the direction of road vehicle traffic control system, traffic flow detection, traffic control system, etc., can solve the problems of redundant data and slow processing, and achieves overcoming complexity, rapid data processing, and easy deployment. Effect

Active Publication Date: 2017-03-22
ZHEJIANG UNIV OF TECH +1
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Problems solved by technology

[0004] The present invention overcomes the shortcomings of the existing massive traffic data processing methods, such as redundant data and slow processing, proposes a method for processing data using the Hadoop platform, and designs a Hadoop-based massive traffic data processing and analysis method to better solve traffic problems. Data processing is slow, and data processing and calculation can be realized quickly to achieve effective road matching and related road flow and various complex calculations, such as specific data calculation of road flow, vehicle speed and intersection diversion

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  • Hadoop-based massive traffic data processing method

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Embodiment Construction

[0027] The massive traffic data processing method based on Hadoop involved in the present invention comprises the following steps:

[0028] 1) Distributed road matching: The data is transmitted to the HDFS data storage system of the Hadoop platform, which is convenient for distributed processing of data. The purpose of road matching is to match valid GPS points to the roads where they are located, and perform accurate traffic statistics. Wherein step 1) specifically includes:

[0029](1.1) Multi-node data processing and calculation: transfer the data file containing taxi information to the HDFS data storage system, order multiple computers to process the data at the same time as independent nodes, including cleaning of taxi data and vector map Correction, etc., the main purpose is to comprehensively eliminate logically erroneous GPS point data, specifically including data with time disorder and speed that does not conform to common sense; in road correction, it mainly solves t...

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Abstract

Provided is a Hadoop-based massive traffic data processing method, which comprises the following steps: 1) distributed road matching, which specifically comprises establishment of a MapReduce framework, trajectory analysis and establishment and expansion of a road network; 2) calculation of road flow and vehicle speed; and 3) road diversion statistics.

Description

technical field [0001] The invention relates to a method for processing massive traffic data. Background technique [0002] In today's big data era, due to the variety of GPS acquisition devices and the diversification of acquisition methods, the traffic data is becoming increasingly large. Traditional methods can no longer satisfy the data analysis. In order to obtain the value contained in the data, various data analysis and mining methods Came into being. [0003] It is difficult to directly extract valuable information from massive data. It has always been the goal of urban intelligent transportation planning to accurately and timely analyze the traffic status and provide high-quality traffic guidance services for travelers. The processing is concentrated on the parallel distributed computing platform, and the traffic data is stream-processed using Hadoop's MapReduce distributed computing framework, and the distributed platform ensures its timeliness and high fault tole...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
CPCG08G1/0125
Inventor 梁荣华李思翟双坡孙国道贡伟
Owner ZHEJIANG UNIV OF TECH
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