Urban travel passenger flow attribute identification method based on multi-source positioning data

Abstract

The invention discloses an urban travel passenger flow attribute identification method based on multi-source positioning data, which comprises the following steps: (1) eliminating noise data of mobilephone signaling data, and improving the data quality; (2) collecting an interest point list of microblogs, and obtaining interest point attribute information of the microblogs in each base station cell; (3) according to the residence time of the user mobile phone signaling information in the researched city, dividing the residence time into resident population or foreign persons; (4) identifyinga daytime residence place and a nighttime residence place of the user according to the residence time of the mobile phone signaling information of the user in each base station cell; And (5) further subdividing the travel group type of the user according to the interest point attribute information of the microblogs in the daytime residence place and the nighttime residence place of the user. According to the method, the urban travel groups of the types of resident population, business office personnel, tourist personnel, college students and the like can be identified, and a good foundation islaid for comprehensively and accurately researching travel characteristics of various urban crowds and scientifically and reasonably predicting urban traffic requirements.

Description

technical field [0001] The invention relates to the technical field of traffic planning, in particular to a method for identifying attributes of urban travel passenger flow based on multi-source positioning data. Background technique [0002] With the acceleration of urbanization in our country, the spatial connection between cities is further strengthened, especially the proportion of floating population in large cities is increasing year by year. As a special component of the total urban population, the travel rules of floating population, such as the number of trips, travel methods, etc. , There is generally a big difference with the travel rules of urban residents, which adds an increasingly heavy load to the city's traffic conditions and management systems. Research on the travel characteristics of floating population and permanent residents is of great significance for scientifically and rationally predicting urban transportation demand and formulating urban transporta...

AI Technical Summary

Problems solved by technology

However, the mobile phone data provided by the operator does not contain social attribute information such as the user's gender, age, occupation, and address. To protect user privacy, the mobile phone number is encrypted, so it is impossible to conduct investigations on the social

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