摘要
城市居民的交通出行是交通研究中的基础问题。结合当前手机应用的特点,以手机应用与无线通信网络数据交互时产生的CI(Cell-ID Identify)定位数据为研究对象来获取居民出行数据。采集了"易信"手机应用2013与2014年共3 241 238条有效的CI定位数据,并对其进行了降维、离散化、去噪预处理。提出将定位数据标准化为0-1数据矩阵,以矩阵运算的形式推导用户出行OD矩阵、各小区出入流量等二次数据的算法模型,并在Matlab中进行了实现。结果表明,相较于遍历数据的循环算法,推导效率有显著提升。提出了推导OD矩阵的完整性与真实性评价指标R,并计算得到2013的R为19.1%,2014为69.3%。发现手机应用日均数据量较大的CI数据具有更高的完整性与真实性(2013年为10.6条,2014年为47.4条),但该指标主要反映所有小区中存在交通出行的整体情况,对各小区的出行行为的完整性与真实性尚需做进一步研究。
travel of Urban residents is one of the fundamental questions in transportation research.According to the characteristics of the current mobile phone application,this paper focuses on extracting residents＇ travel data from CI（Cell-ID Identify）location data generated during the interaction between mobile phone application and wireless communication network.A total of 3 241 238 CI positioning data in 2013 and 2014 has been collected from ＂ Yi Xin＂ App,which is then preprocessed through dimensionality reduction,discretization and de-noising.This paper develops an efficient matrix operation algorithm to extract origin/destination information and inbound and outbound traffic flow data of each residential area based on the conversion of CI positioning data into standardized 0-1 matrices.Matlab is used to implement this algorithm.The results show that,comparing to circulation algorithm of data traversal search,this algorithm can achieve a higher efficiency which shorten the time from days to minutes.An index Rhas been presented to evaluate the integrity and authenticity of the derivate users′OD matrices.The index Rof OD matrices is 19.1% in 2013,and 69.3% in 2014.The results indicate that the CI positioning data with higher daily data amount（10.6 in 2013 and 47.4 in 2014）has higher integrity and authenticity.However,this index only reflects the overall condition of trips from all residential areas,and the fact if this index can fully and truthfully represent travel behavior of each individual traffic analysis zone should be further studied.
出处
《交通信息与安全》
2015年第6期40-47,共8页
Journal of Transport Information and Safety
基金
上海市科委2014年度联盟能力提升建设项目(批准号:14DZ0511300)
国家自然科学基金项目(批准号:61074139)资助
关键词
交通大数据
交通出行
交通OD数据
移动定位数据
CI移动定位技术
手机应用
traffic big data
traffic trips
traffic OD data
mobile positioning technology
CI-based mobile localization technology
mobile phone application
