Feature recognition method for different travel activities based on mobile phone positioning data

A technology of positioning data and feature recognition, applied in the directions of location information-based services, network data management, data processing applications, etc., can solve the problem of inability to effectively generate a one-day travel activity chain, lack of time-space correlation OD integration, and ignoring the overall travel activity chain. characteristics, etc., to achieve the effect of flexible sampling time, low cost, and large information samples

Inactive Publication Date: 2021-01-12
广州市交通规划研究院
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AI Technical Summary

Problems solved by technology

When the purpose of travel is judged in OD analysis, there is a lack of effective integration of time and space related OD travel, and it is impossible to effectively generate a one-day travel activity chain
Therefore, the travel activity purpose discrimination technology based on clustering technology or POI identification technology will ignore the overall characteristics of a complete travel activity chain in a day, resulting in misjudgment of travel activities that do not meet the characteristics of traffic travel OD activities

Method used

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  • Feature recognition method for different travel activities based on mobile phone positioning data
  • Feature recognition method for different travel activities based on mobile phone positioning data
  • Feature recognition method for different travel activities based on mobile phone positioning data

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Embodiment Construction

[0028] Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in detail, refer to accompanying drawing figure 1 , the specific implementation steps are as follows:

[0029] Step 1: Obtain mobile phone signaling data and Internet access data. Mobile phone signaling data and Internet access data sample such as table 1, described mobile phone signaling data includes user portrait tag attribute data, user portrait tag attribute data sample such as table 2;

[0030] Table 1 Sample of mobile phone signaling data and Internet access data

[0031]

[0032] Table 2 User portrait tag attribute data sample

[0033]

[0034] Step 2: Using the mobile phone signaling data and Internet access data collected in step 1, extract the mobile phone trigger data within three months to judge the job and residence, determine the LiveLoc of the job and residence and the WorkLoc of the employment, and obtain the distribution characteristics...

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Abstract

The invention provides a feature recognition method for different travel activities based on mobile phone positioning data. The method comprises the steps of carrying out the job-house and life travelpurpose time-space kernel clustering analysis and time-space correlation feature analysis of OD residence points of the mobile phone positioning data, forming different travel activity purpose travelchains with time-space correlation features, and carrying out the pairing of the travel chains; performing verification and algorithm optimization on the obtained time-space stationary point set, performing analysis on crowds with different travel activity target features, and finally forming an OD matrix travel table based on a traffic cell, thereby providing big data support meeting the features of a space-time travel activity chain for traffic planning and traffic demand management. According to the invention, the respective advantages of the time-space activity correlation analysis and the OD matrix generation table are combined to finally form the stationary point sequence with time-space activity target features, so that the rationality and accuracy of OD matrixes of different travel targets of traffic are further improved, and the cost is effectively reduced.

Description

technical field [0001] The invention relates to the technical field of traffic planning and traffic demand management, and specifically relates to a method for identifying characteristics of different travel purposes based on mobile phone positioning data, which can provide big data support for traffic planning and traffic demand management to meet the characteristics of different travel purposes. Background technique [0002] The traditional traffic travel survey is a process of statistical analysis based on individual traffic travel survey data. It needs to conduct individual sampling of different groups of people to investigate travel purposes, travel modes, travel time, travel distance, etc. The analysis and processing results can reflect urban traffic demand and Spatiotemporal distribution characteristics. [0003] The analysis and processing process based on traditional traffic travel surveys requires a lot of manpower, material resources, funds and time, and cannot be...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q50/26H04W4/029H04W8/18
CPCG06Q30/0201G06Q50/26H04W4/029H04W8/18
Inventor 马小毅李彩霞景国胜金安陈先龙陈嘉超胡卓良宋程刘明敏丁晨滋张科
Owner 广州市交通规划研究院
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