Novel shared public transport service area selection method based on mobile phone signaling data

Abstract

The invention discloses a novel shared public transport service area selection method based on mobile phone signaling data, and the method specifically comprises the steps: 1), obtaining the complete travel feature data of residents through employing a data mining algorithm based on the features of mobile phone user signaling data obtained by a communication operator; 2) through extracting mobile phone user information of a plurality of continuous workdays, carrying out occupational and residential place discrimination and commuting behavior identification on base stations periodically appearing in a specific time period; (3) calibrating and classifying the base stations by using an improved DBSCAN method by calculating the activeness of the base stations in different time periods of a workday and combining the rich geographical location information and traffic information of the base stations, and dividing traffic cells; and 4) selecting a novel shared public transport service area by utilizing a qualitative and quantitative comprehensive analysis mode according to the population density of each traffic zone, the travel volume between the OD pairs of the traffic zones, the mass center distance, the existing public transport network supply condition and the road condition.

Description

technical field [0001] The invention belongs to the technical field of communication and the field of public transportation, in particular to a method for selecting a new shared public transportation service area based on mobile phone signaling data. Background technique [0002] The development and popularization of mobile communication technology and Internet technology have made mobile phone signaling data one of the main sources of urban traffic data. It has the characteristics of strong availability, large sample size, high reliability, and continuous observation, which has attracted the attention of many scholars. [0003] The traditional way to obtain demand for new shared public transportation is mainly through surveys on residents’ trips, including home visit surveys and telephone surveys. This process requires a lot of manpower, material resources, and energy to complete the survey and carry out data integration and processing. In recent years, communication equip...

AI Technical Summary

Problems solved by technology

However, the demand for personalized transportation brought about by urban development continues to increase. The design of the demand-responsive new public transportation system is not conducive to the improvement of the overall level of the urban public transportation system, and may even lead to further increase in urban traffic pressure, and the service quality will also be affected.

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