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Road network traffic operation analysis method based on Spark

An analysis method and a technology of traffic operation status, applied in the field of intelligent transportation, can solve the problems of lack of scientificity and reliability, and less real-time information feedback of the road network, and achieve the effects of overcoming timeliness problems, reducing computing time, and improving efficiency

Inactive Publication Date: 2019-06-18
CHANGAN UNIV
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Problems solved by technology

[0003] At this stage, most of the research is mainly focused on the road network operation analysis based on the historical data of the expressway network, and the real-time information feedback on the road network is less; among them, some studies are based on the real-time speed in the road network to analyze the road network. Running status analysis, lack of science and reliability

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  • Road network traffic operation analysis method based on Spark
  • Road network traffic operation analysis method based on Spark
  • Road network traffic operation analysis method based on Spark

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[0054] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0055] Analysis method provided by the invention comprises the following steps:

[0056] 1) First, use 5 PCs to build a Spark big data machine learning platform including a master node and four slave nodes. The master node serves as the control node of the big data machine learning platform, and the slave node serves as the working node of the big data machine learning platform. Each node communicates with each other through Gigabit Ethernet in a local area network.

[0057] The Linux (ubuntu 12.04) operating system is installed on all nodes, and the software required in the process of building...

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Abstract

The invention relates to a road network traffic operation analysis method based on Spark, is based on real-time traffic flow data and constructs a road network traffic operation situation discrimination model in combination with the k-means and random forest algorithm. Distributed file system storage and an elastic distributed data set are selected to process traffic data in parallel, and real-time discrimination of the road network traffic operation status is realized. The method is advantaged in that a Spark big data machine learning platform is utilized, in combination with the distributedk-means algorithm for cluster analysis, a timeliness problem of the traditional k-means algorithm in the case of big data is improved, discrimination of the road network traffic operation status is realized, the analysis result can provide real-time and reliable road network operation status analysis services for highway management departments, moreover, the theoretical basis is provided for establishing an intelligent highway control platform.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a Spark-based road network traffic operation analysis method established by applying big data analysis and mining technology. Background technique [0002] With the in-depth development of intelligent transportation system (Intelligent Transportation System, ITS) research, the scale and complexity of road traffic data are growing explosively, showing the "6V" characteristics of big data. However, in the field of expressways, the storage and processing of traffic data still adopts the traditional serialization method. Due to the huge amount of data and complex data structure, the calculation completion time cannot be applied to actual scenarios. Therefore, using parallel and distributed data processing technology to improve the level of traffic information processing has become the mainstream of current traffic big data platform research. It is an urgent industry demand ...

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Application Information

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IPC IPC(8): G08G1/01G06K9/62
Inventor 钱超杨孟朱熹许宏科刘冬伟
Owner CHANGAN UNIV
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