基于手机信令数据的流动人口出行特性分析方法研究

发布时间：2018-03-12 10:12

本文选题：手机信令数据　切入点：流动人口　出处：《东南大学》2016年硕士论文　论文类型：学位论文

【摘要】：伴随着我国的城镇化进程,城市间的空间联系进一步加强,流动人口数量逐年增多。作为城市总人口中特殊的组成部分,流动人口的出行特性与城市居民出行规律一般有较大的差异,因此,流动人口的调查和出行特性研究对于科学合理化制定城市对外交通发展战略,进行城市交通方式整合和交通网络规划具有极其重要的意义。近年来,随着移动通信技术的快速发展和手机的广泛普及,基于移动网络手机信令数据的交通信息采集技术正越来越被各个城市的交通主管部门重视和应用。通过手机信令数据可以获取某位匿名用户某时刻的空间位置和随时间变化移动的情况,具有时间、空间的多重维度,成为了人口调查及其出行特性研究的一种新的技术选择方向。本文将立足于手机信令数据,对流动人口识别及出行特性分析方法进行研究。首先,为了对手机信令数据产生的机制有一个全面深入的了解,本文对GSM通信网络和手机定位原理进行了简要的介绍,对手机信令数据和基站数据进行了深入的解读,并分析了手机信令数据的特性。在此基础上结合“流动人口”和“出行”的定义分析了手机信令数据应用于流动人口出行特性分析方法研究的适用性。其次,根据流动人口的定义,确定研究范围和研究对象,通过研究范围内基站位置和信令数据的匹配提取了目标用户和目标数据,并借鉴已有研究,建立了一种更为完善的多层次数据处理方法,对数据进行过滤、去噪处理,进而得到高质量数据,以便开展后续的工作。再次,建立流动人口识别模型。根据手机用户出行轨迹,将提取的目标用户进行分类,并确定流动人口种类。将流动人口识别问题转化为轨迹点在不同区域内出现的顺序问题,并设计算法提取流动人口,并通过数据扩样,估计全域流动人口。然后,研究流动人口出行特性分析方法。通过分析用户的出行轨迹,确定时间闽值、距离阈值,设计出一种基于时空聚类的出行轨迹点状态识别算法,从而将轨迹点划分为停驻点、运动点。进而建立了到达时间、离开时间、停留时间、出行次数、出行距离等多种出行特征指标分析方法。最后,总结研究方法的创新和不足,并对后续研究提出展望。
[Abstract]:Along with the urbanization process of our country, to further strengthen the city spatial connection between, the number of floating population increased year by year. As a special part of the city's total population, the floating population and city residents travel characteristics of general travel rules are different, therefore, the investigation and study of the travel characteristics of floating population for scientific development the city's traffic development strategy, has important significance of integration of city traffic and transportation network planning. In recent years, with the popularity of the rapid development of mobile communication technology and mobile phone, the traffic information collection technology based on mobile network mobile phone signaling data is becoming more and more competent departments of transportation in each city spatial attention and application. Through the mobile phone signaling data can obtain an anonymous user at a time and time varying mobile, with time, space The multiple dimensions, become a kind of new technology to choose the direction of investigation and study the travel characteristics of population. This paper will focus on the mobile phone signaling data, analysis method for floating population identification and travel characteristics of research. First of all, to the occurrence mechanism of mobile phone signaling data to have a comprehensive understanding, this paper gives a brief the introduction of GSM communication network and mobile phone positioning principle of mobile phone signaling data and base station data in-depth interpretation, and analysis of the characteristics of mobile phone signaling data. On the basis of the definition of "floating population" and "travel" analyzes the application of the method of research and application of mobile phone signaling data on population travel characteristics analysis. Secondly, according to the definition of floating population, determine the scope of the study and the research object, through the matching in the range of base station location and signaling data extraction and target users The target data, and based on existing research, a treatment method of multi-level data well established, on data filtering denoising, and get high quality data, in order to carry out follow-up work. Once again, the establishment of floating population identification model. According to the mobile phone users travel path, the extracted target user classification sure, the floating population and floating population. The species identification problem into the order of the track points appear in different areas, and the design of extraction algorithm of floating population, and through data sampling expansion, global estimation of floating population. Then, analysis method of floating population travel characteristics. Through the analysis of user travel path, determine the time threshold, the distance threshold, designed a travel path point state recognition algorithm based on spatiotemporal clustering, which will be divided into the track point, moving point. Then established the arrival time from Several travel characteristics index analysis methods such as opening time, residence time, trip times and travel distance are summarized. Finally, the innovation and deficiency of research methods are summarized, and future research is prospected.

【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U491

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