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Floating car data and road matching method based on MapReduce calculation frame

A floating car data and computing framework technology, applied in road vehicle traffic control systems, traffic flow detection, instruments, etc., can solve the problems of no congestion information, difficult analysis and learning algorithms, etc., to improve performance and scalability, complex Effects of speed reduction, processing capacity and processing scale increase

Active Publication Date: 2015-03-11
JIANGSU CAS JUNSHINE TECH
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Problems solved by technology

Unfortunately, the government departments of many cities have not recorded the historical congestion conditions of various roads. Without historical congestion information, it is difficult to apply corresponding analysis and learning algorithms to obtain the required mode information of congestion information.

Method used

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  • Floating car data and road matching method based on MapReduce calculation frame
  • Floating car data and road matching method based on MapReduce calculation frame

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Embodiment Construction

[0023] The present invention will be further described below in conjunction with specific drawings and embodiments.

[0024] In order to ascertain the problem of road congestion, the present invention adopts the scheme of using floating car data to calculate the road congestion situation. The main component of the floating car is a taxi. Due to the characteristics of the randomization of the taxi's driving route, the data it collects is spread across almost all roads in the city. There is a large amount of information for analyzing and calculating the congestion situation of the road at that time.

[0025] The invention uses a distributed column storage database as a storage medium and utilizes MapReduce as its distributed computing framework.

[0026] In the system of the present invention, the historical data of more than 20,000 floating cars for one year are collected, and the generation frequency of the data is one piece every 30 seconds. The key fields in the floating c...

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Abstract

The invention provides a floating car data and road matching method based on a MapReduce calculation frame. The method comprises the steps: step 1, dividing a road network into grids; step 2, positioning line segments on the grids by using the MapReduce distributed calculation frame; step 3, positioning floating car data on the grids by using the MapReduce distributed calculation frame; and step 4, positioning points representing floating car data on the line segments in the same grid by using the MapReduce distributed calculation frame. According to the floating car data and road matching method based on the MapReduce calculation frame, the complexity of the matching algorithm in the system is reduced as much as possible by using a distributed storage and calculation frame and a data cutting technology, so that the data processing capacity and processing scale can be improved greatly.

Description

technical field [0001] The invention relates to the field of traffic control, in particular to an analysis method for road congestion. Background technique [0002] Road congestion has become an important factor restricting economic development, and has greatly reduced the quality of life of the people. How to effectively solve the problem of traffic congestion is not just about building more roads and diverting more traffic. The corresponding road congestion analysis and congestion mode prediction are also of great practical significance. Unfortunately, the government departments of many cities have not recorded the historical congestion conditions of various roads. Without historical congestion information, it is difficult to apply corresponding analysis and learning algorithms to obtain the required mode information of congestion information. Contents of the invention [0003] The purpose of the present invention overcomes the deficiencies in the prior art, and provid...

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Application Information

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IPC IPC(8): G08G1/01
CPCG08G1/0112
Inventor 刘斌程子轩赵旦谱王艳军台宪青
Owner JIANGSU CAS JUNSHINE TECH
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