Study On Methods Of Analyzing The Floating Population Trip Characteristics Based On Phone Signaling Data

With the urbanization process's acceleration, contact between cities is to further strengthen, and the floating population increases year by year. As a special part of city population, the travel characteristics of floating population have differences with urban resident.Therefore, the study on investigation and travel characteristics of floating population is of great significance for formulating urban external traffic development strategy scientifically and reasonably and making transportation integration and traffic network planning.In recent years, with the rapid development of mobile communication technology and the widespread popularity of mobile phone, mobile network traffic information collection technology based on cell phone signaling data is more and more valued and applied by the transportation departments.Phone signaling data can obtain the space position at some time and movements over time of anonymous users with the multiple dimensions of time and space, becoming a new kind of technology choice direction of demographic census and trip characteristics research.This article studies identification and travel characteristics analysis's methods of the floating population based on mobile phone signaling data,First, in order to understand the mechanism of mobile signaling data comprehensively, this paper has carried on a brief introduction for the GSM communication network and mobile phone positioning principle, and makes a deep interpretation and then analyzes the characteristics of the mobile phone signaling. On the basis of this, the applicability analysis has been done for the mobile phone signaling data applied to travel characteristic analysis of the floating population combined with the definition of "floating population" and "travel".Secondly, the research determines the range and object of according to the definition of floating population, and then extracts the target users and target data by matching base station location and signaling data. On the basis of existing research, the paper establishes a more perfect multi-level data processing method to filter and remove the noises of data, and therefore gets high quality data which lays the foundation for the follow-up work.The next, the paper establishes a recognition model of the floating population. According to users' travel path, the target users are classified into 6 kinds, and confirming the 3 types of floating population. So, the recognition of floating population can be converted to analyze order problems of track points in different area. And then design algorithms to extract floating population. Finally, estimate of the floating population through the data sampling expansion.Then, the study focus on the analysis method of trip characteristics of the floating population. Through the analysis of the travel path of users, determining the time threshold, distance threshold, and then designing algorithm to recognize the travel track points'state based on space-time clustering, which will divide track points into stagnation or moving point. On this basis, the study establishes the analysis method of a variety of travel indicators, including arrival time, leaving time, residence time, travel frequency, travel distance, etc.Finally, the paper summarizes the innovation and the insufficiency of research methods, and puts forward prospect for further research.