Method and system for identifying bus network coverage blind area based on mobile phone signaling and big data analysis

Abstract

The invention provides a method and a system for identifying a bus network coverage blind area based on mobile phone signaling and big data analysis, wherein the method and the system are used for positioning actual movement tracks of travel destinations such as actual residence, employment, entertainment and the like of a user individual by utilizing mobile phone signaling data of the user individual, matching a real travel route of a user without sampling investigation, and improving the user experience; a starting point, a destination point and actual passing road sections of bus users arerecognized through mobile phone signaling, all-area bus requirements are obtained to be used for recognizing bus network coverage blind areas, and the recognition accuracy is improved. In a bus demandidentification clustering process, on one hand, a mobile phone signaling track provided by the individual user is used as original data to identify a track segment adopting bus travel, and on the other hand, GPS data of the starting point and the destination of taxi travel provided by a public taxi is collected to serve as transfer bus demands; and the track segment of the demand of bus travel isidentified, so that a complete bus travel demand thermodynamic diagram is formed, and the accuracy and comprehensiveness of identification are improved.

Description

technical field [0001] The present invention relates to the technical field of intelligent transportation, especially the identification of bus coverage blind spots, and specifically relates to a method and system for identifying bus coverage blind spots based on mobile phone signaling and big data analysis. Background technique [0002] The construction of urban public transportation often lags behind the speed of infrastructure construction brought about by urban expansion, resulting in insufficient transportation resources in many newly-built functional areas, a large number of public transportation coverage blind spots, and the problem of travel difficulties is increasing day by day. [0003] The layout of new bus lines requires scientific passenger flow demand research. The traditional method is sampling questionnaire survey, including online and offline methods. This method not only has the problem of time-consuming and laborious, but also leads to low data quality due...

AI Technical Summary

Problems solved by technology

The traditional method is sampling questionnaire survey, including online and offline methods. This method not only has time-consuming and labor-intensive problems, but also leads to low data quality due to the non-standard filling of the respondents.

Another traditional method is to use the four-stage method to calculate OD. However, because the model is based on the survey data of previous years and is derived using a theoretical model, it is not derived in combination with actual road conditions and actual living conditions, and the accuracy of the data is not good.

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