基于手机信令数据的轨道交通客群特征研究
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摘要
根据手机信令数据的通讯特征,提出了测度地下轨道交通站点客流的原理与技术方法,并通过基站识别软件实测数据来匹配轨道交通各站点与其进出口附近的地上与地下基站,确保准确性。在此基础上,以杭州市为例,将手机信令测得的数据与IC卡数据相比较,结果显示,两者拟合程度较高,说明该方法测度轨道交通客流有效性强。进一步充分利用手机信令可准确识别轨道用户的优势,根据乘客在轨道交通系统内外部的活动信息,继续探究该方法在轨道交通乘客职住地分布以及各站点换乘客流量等方面的应用,为优化轨道交通规划设计与运营管理提供支撑。
According to the communication characteristics of mobile phone data, a principle and technical method of measuring passenger flow in underground rail transit is proposed, while a software of identifying base stations is also used. Thus it is possible for us to match each rail transit station with all the base stations around it. In addition, the case study of Hangzhou indicates that the result estimated by mobile phone data have a high degree of fitting for the IC cards records, which means this method is effective. Moreover, since this method has a good advantage of identifying passengers of underground rail transit accurately, all information inside or outside of the rail transit is used to explore more applications, such as studying the distribution of passengers' residential and occupational areas and the numbers of interchange passengers. This research establishes a foundation for optimizing rail transit planning, design and operation management.
According to the communication characteristics of mobile phone data, a principle and technical method of measuring passenger flow in underground rail transit is proposed, while a software of identifying base stations is also used. Thus it is possible for us to match each rail transit station with all the base stations around it. In addition, the case study of Hangzhou indicates that the result estimated by mobile phone data have a high degree of fitting for the IC cards records, which means this method is effective. Moreover, since this method has a good advantage of identifying passengers of underground rail transit accurately, all information inside or outside of the rail transit is used to explore more applications, such as studying the distribution of passengers' residential and occupational areas and the numbers of interchange passengers. This research establishes a foundation for optimizing rail transit planning, design and operation management.
引文
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[8]王利雷.基于手机信令数据的城市轨道交通客流出行信息提取方法研究[D].成都:西南交通大学,2018.
[2]杜亚朋.基于手机信令数据的居民轨道交通通勤出行研究[D].重庆:重庆邮电大学,2017.
[3]方勇.手机信令数据在轨道站点客流与土地利用关联性研究中的应用[D].深圳:深圳大学,2017.
[4]杨彬彬.基于手机信令数据的城市轨道交通客流特征研究[D].南京:东南大学,2015.
[5]余东豪.基于手机数据的轨道交通用户出行特征分析方法[D].南京:东南大学,2017.
[6]王建华.GSM网位置更新成功率低的案例分析[J].邮电设计技术,2010(5):49-52.
[7]宋少飞,李玮峰,杨东援.基于移动通信数据的居民居住地识别方法研究[J].综合运输,2015,37(12):72-76.
[8]王利雷.基于手机信令数据的城市轨道交通客流出行信息提取方法研究[D].成都:西南交通大学,2018.