基于手机信令数据的居住和出行特征分析 —以深圳市为例 丘建栋',林青雅,李强2 深圳市城市交通规划设计研究中心有限公司,广东省深圳市,518021:2.广东省交通信息工程技术研究中心,广东省深圳 市,518021 【摘要】:手机信令数据样本量大、数据客观、全面、采样不会有很明显的倾向性,且数据 具有较强的时空持续性,可以观测到交通出行整个过程,是任何其它数据源无法比拟的。用 手机信令数据分析城市交通运行特征,弥补了传统的交通调查周期性长、工作量大、样本量 少和花费高的特点。本文研究利用手机信令数据的时空信息,对城市交通出行特征进行可视 化和科学分析,分析结果显示,原特区内与特区外仍有较强职住通勤吸引;住在东莞、惠州, 职在深圳的人,居住和就业位置基本在城市间交界地带;早高峰出行形成明显东西向、南北 向通道。分析所得结果可为交通规划和运营部门提供可靠的依据。 【关键词】:手机信令数据、数据质量检查、大数据分析应用、可视化 Residential and Travel characteristics analysis based on Mobile phone signaling Data-A Case in Shenzhen city Jiandong Qiu, Qingya Lin, Qiang Li 1. Shenzhen Urban Transport Planning Center Co, Ltd, Shenzhen 518021, Guangdong, China; 2. Traffic Information Engineering Technology Research Center of Guangdong Province, Shenzhen 518021, Guangdong, China) There is no obvious tendency for the data of mobile phone signaling data to be objective comprehensive and sampling. The data has strong spatiotemporal continuity and can be observed in the whole process of traffic travel, which is unmatched by any other data source. Using mobile phone signaling data to analyze the characteristics of urban traffic operation, make up for the traditional traffic survey cyclical long, heavy workload, sample size and high cost characteristics This paper studies the use of space-time information of mobile signaling data to visualize and analyze the characteristics of urban traffic travel. The analysis shows that there is still a strong job commuting attraction in the original SAR and the sEz; most people living in Dongguan, Huizhou, working in Shenzhen, living and employment in the basic position of the junction of the city; early peak of the formation of a clear east-west, north-south to the channel. Analyzing the results provides a reliable basis for transport planning and operations Cell Phone Signaling Data, Check Data Quality, Data Quality Inspection, Big Data Analysis 科技计划项目(GGFW2016033017241891),深圳市战略性新兴产业发展专项(深发改(2017)550号) 高级工程师,研究方向:交通大数据、交通模型,E-mal. guid@sutpc com 女,本科,职员,研究方向:大数据分析,Ema1160193194@ gecom基于手机信令数据的居住和出行特征分析 ——以深圳市为例 丘建栋 1 ，林青雅* ，李强 2 1.深圳市城市交通规划设计研究中心有限公司，广东省深圳市，518021；2. 广东省交通信息工程技术研究中心，广东省深圳 市，518021 【摘 要】：手机信令数据样本量大、数据客观、全面、采样不会有很明显的倾向性，且数据 具有较强的时空持续性，可以观测到交通出行整个过程，是任何其它数据源无法比拟的。用 手机信令数据分析城市交通运行特征，弥补了传统的交通调查周期性长、工作量大、样本量 少和花费高的特点。本文研究利用手机信令数据的时空信息,对城市交通出行特征进行可视 化和科学分析，分析结果显示，原特区内与特区外仍有较强职住通勤吸引；住在东莞、惠州， 职在深圳的人，居住和就业位置基本在城市间交界地带；早高峰出行形成明显东西向、南北 向通道。分析所得结果可为交通规划和运营部门提供可靠的依据。 【关键词】：手机信令数据、数据质量检查、大数据分析应用、可视化 Residential and Travel Characteristics Analysis Based on Mobile Phone Signaling Data——A Case in Shenzhen City Jiandong Qiu1 , Qingya Lin* , Qiang Li2 1. Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518021, Guangdong, China; 2. Traffic Information Engineering & Technology Research Center of Guangdong Province, Shenzhen 518021, Guangdong, China） Abstract There is no obvious tendency for the data of mobile phone signaling data to be objective, comprehensive and sampling. The data has strong spatiotemporal continuity and can be observed in the whole process of traffic travel, which is unmatched by any other data source. Using mobile phone signaling data to analyze the characteristics of urban traffic operation, make up for the traditional traffic survey cyclical long, heavy workload, sample size and high cost characteristics. This paper studies the use of space-time information of mobile signaling data to visualize and analyze the characteristics of urban traffic travel. The analysis shows that there is still a strong job￾commuting attraction in the original SAR and the SEZ; most people living in Dongguan, Huizhou, working in Shenzhen, living and employment in the basic position of the junction of the city; early peak of the formation of a clear east-west, north-south to the channel. Analyzing the results provides a reliable basis for transport planning and operations. Keywords Cell Phone Signaling Data, Check Data Quality, Data Quality Inspection, Big Data Analysis 1 基金项目:深圳市科技计划项目（GGFW2016033017241891），深圳市战略性新兴产业发展专项（深发改〔2017〕550 号） 1 丘建栋(1982-)，男，硕士，高级工程师，研究方向：交通大数据、交通模型，E-mail: qiujd@sutpc.com *林青雅，女，本科，职员，研究方向：大数据分析，E-mail:1160193194@qq.com