| With the development of mobile communication technology,the use value of mobile signaling data is increasing.Mobile signaling data can be used to locate mobile phone users,thus playing a role in various research fields that need location data.Especially in the field of traffic investigation,mobile signaling data has gradually begun to emerge.This paper mainly uses quantitative research method to study how to identify and optimize commuting routes using mobile signaling data in Xiamen.This paper analyses some defects of mobile signaling data,such as"PingPang" switching phenomenon,"base station drift" phenomenon and data missing phenomenon,and puts forward corresponding solutions.At the same time,this paper also clarifies the reasons for merging the original mobile signaling data records and the fields that should be retained in the merging,mainly in order to solve the data defects and reduce the subsequent data processing volume.On this basis,this paper uses the time threshold method to identify the residence and workplace of mobile phone users,and carries out corresponding analysis and verification to ensure the effectiveness of this identification method.Based on the above research results,combined with the matching results of base station and road network,this paper uses the improved A*algorithm to identify and optimize the mobile phone users’ commuting lines.The conclusion is that the mobile phone users’ commuting lines can be identified by using 2G and 3G fusion signaling data under sufficient sample size(usually one month’s signaling data volume),and the line can be carried out.Optimize.The research content of this paper is a relatively basic part of traffic research using mobile signaling data.The research results can not only guide mobile phone users to choose commuting routes,but also provide new ideas for traffic departments to carry out population distribution and peak road flow measurement in the morning and evening. |
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