基于公交IC卡和GPS数据的居民公交出行OD矩阵推导与应用
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摘要
随着我国城市社会经济以及物质文化生活水平的不断提升,快速城市化、机动化现象愈演愈烈；加之,城市人口不断增加,居民交通需求与日俱增,城市交通拥堵状况日益加剧。大力优先发展城市公共交通系统是我国城市缓解城市交通拥堵状况的根本出路和必然选择。公共交通基础数据资源是进行科学、有效的城市公共交通规划与管理运营决策的基础保障和关键。而传统基础数据采集采用人工调查的方式进行,不仅耗费大量的人力、物力、财力资源,还存在着调查数据样本量低、数据精度差、不能及时进行数据更新的固有缺陷。随着现代信息技术的发展,大量高科技硬件设施如公交刷卡收费系统、公交GPS系统等应用于城市公共交通系统之中,而所采集到的数据信息并未进行深度的挖掘与应用。本文基于公交IC卡和GPS数据进行城市居民公交出行OD矩阵的推导与应用,则实现了深度的公交基础数据挖掘与应用。
首先,针对城市公交IC卡收费系统的国内外相关研究应用状况进行综述分析,分别从城市公交IC卡的推广应用、公交数据仓库构建与数据挖掘技术、公交出行OD矩阵反推、公交运营与规划应用4个方面展开。总结城市公共交通基础数据的采集技术,主要分为传统人工调查采集技术和基于现代信息技术的公交基础数据采集技术2类。
城市公交数据仓库构建与数据挖掘技术、城市公交居民出行OD矩阵推导是本文的核心与关键。基于城市公交IC卡、GPS数据源,分别建立了基于公交IC卡数据的数据仓库结构体系、基于公交IC卡和GPS数据的数据仓库结构体系；并在此基础上,构建了包含数据仓库模块、数据挖掘工具模块、数据逻辑分析模块、用户控制模块4层结构的数据挖掘结构体系。城市公交居民出行OD矩阵推导主要包括公交站间OD矩阵推导、公交出行OD矩阵生成、公交出行OD矩阵校验3方面的内容。其中,公交站点OD矩阵推导是本章的核心研究内容,分别从上车站点推导、下车站点推导、公交换乘分析以及站间出行OD矩阵生成4个方面展开,并详细阐述了推导上车站点的基于公交IC卡数据和调度信息的聚类分析法、基于公交IC卡和GPS数据的时刻匹配分析法,推导下车站点的公交站点吸引权法、基于单个公交乘客的出行链分析法。
最后,基于已挖掘的信息进行公交运营与规划的决策应用分析。分别从城市公交动态特性分析、公交服务质量分析、公交出行特征分析3个方面进行。
Along with continuously upgrade of Chinese social, economic and living level, rapid urbanization and motorization phenomenon are more and more serious. Moreover, the uninterrupted increase of urban population and traffic demand make urban traffic congestion status more and more severe. Giving great priority to the development of urban public transportation system is the fundamental way and inevitable choice to relieve urban traffic congestion. Public transportation basic data resources are the basic guarantee and key to carry out scientific and effective urban public transportation planning and management decision-making. However, traditional basic data collection method is artificial investigation, which not only takes a lot of manpower, material and financial resources, but also exist several inherent defects such as a low sample survey data, poor data accuracy and no data updated in a timely manner. With the development of modern information technology, a large number of high-tech hardwares such as bus IC card payment system, bus GPS system being used in the public transportation system, but the collected data hasn't been mined and applied deeply. Based on the public transportation IC card and GPS data to conduct urban public transportation OD matrix inference and application, the paper has carried out public transportation basic data mining and application more deeply.
Firstly, based on the research and application status of urban public transportation IC card at home and abroad, the literature review has been divided into four parts including urban public transportation IC card application, urban public transportation data warehouse and data mining technology application, research on urban public transportation trip OD matrix inference, urban public transportation operation and planning application based on the data mining information. The urban public transport data collection technology has been divided into traditional manual survey collection technology and urban public transport data collection techonlogy based on modern information technology two parts.
Urban public transportation data warehouse and data mining technology and urban public transportation trip OD matrix inference are core and key. Based on public transportation IC card and GPS data sources, data warehouse structure system based on based on bus IC card and data warehouse structure system based on based on bus IC card and GPS data have been set up. And on this basis, the data mining structure system has been built including data warehouse module, data mining tool module, data logic analysis module and user control module four layers. Urban public transportation trip OD matrix inference has been divided into three parts including urban public transportation station OD matrix inference, urban public transportation trip OD matrix generation and urban public transportation trip OD matrix calibration. Among them, public transportation station OD matrix inference is the core content of the chapter, including public transport boarding station inference, public transportation alighting station inference and public transport transfer analysis and public transportation station OD matrix generation. The boarding station inference method is respectively cluster analysis method based on public transportation IC card data and scheduling information, time matching method based on public transportation IC card data and GPS data. And the alighting station inference method is respectively public transportation station attracting weight method, trip chain analysis method based on a single bus passenger.
Finally, the public transportation operation and planning decisions have been analyzed based on the mined information. There are three parts such as urban public transportation dynamic characteristics analysis, urban public transportation service quality analysis and urban public transportation trip characterstics analysis.
首先,针对城市公交IC卡收费系统的国内外相关研究应用状况进行综述分析,分别从城市公交IC卡的推广应用、公交数据仓库构建与数据挖掘技术、公交出行OD矩阵反推、公交运营与规划应用4个方面展开。总结城市公共交通基础数据的采集技术,主要分为传统人工调查采集技术和基于现代信息技术的公交基础数据采集技术2类。
城市公交数据仓库构建与数据挖掘技术、城市公交居民出行OD矩阵推导是本文的核心与关键。基于城市公交IC卡、GPS数据源,分别建立了基于公交IC卡数据的数据仓库结构体系、基于公交IC卡和GPS数据的数据仓库结构体系；并在此基础上,构建了包含数据仓库模块、数据挖掘工具模块、数据逻辑分析模块、用户控制模块4层结构的数据挖掘结构体系。城市公交居民出行OD矩阵推导主要包括公交站间OD矩阵推导、公交出行OD矩阵生成、公交出行OD矩阵校验3方面的内容。其中,公交站点OD矩阵推导是本章的核心研究内容,分别从上车站点推导、下车站点推导、公交换乘分析以及站间出行OD矩阵生成4个方面展开,并详细阐述了推导上车站点的基于公交IC卡数据和调度信息的聚类分析法、基于公交IC卡和GPS数据的时刻匹配分析法,推导下车站点的公交站点吸引权法、基于单个公交乘客的出行链分析法。
最后,基于已挖掘的信息进行公交运营与规划的决策应用分析。分别从城市公交动态特性分析、公交服务质量分析、公交出行特征分析3个方面进行。
Along with continuously upgrade of Chinese social, economic and living level, rapid urbanization and motorization phenomenon are more and more serious. Moreover, the uninterrupted increase of urban population and traffic demand make urban traffic congestion status more and more severe. Giving great priority to the development of urban public transportation system is the fundamental way and inevitable choice to relieve urban traffic congestion. Public transportation basic data resources are the basic guarantee and key to carry out scientific and effective urban public transportation planning and management decision-making. However, traditional basic data collection method is artificial investigation, which not only takes a lot of manpower, material and financial resources, but also exist several inherent defects such as a low sample survey data, poor data accuracy and no data updated in a timely manner. With the development of modern information technology, a large number of high-tech hardwares such as bus IC card payment system, bus GPS system being used in the public transportation system, but the collected data hasn't been mined and applied deeply. Based on the public transportation IC card and GPS data to conduct urban public transportation OD matrix inference and application, the paper has carried out public transportation basic data mining and application more deeply.
Firstly, based on the research and application status of urban public transportation IC card at home and abroad, the literature review has been divided into four parts including urban public transportation IC card application, urban public transportation data warehouse and data mining technology application, research on urban public transportation trip OD matrix inference, urban public transportation operation and planning application based on the data mining information. The urban public transport data collection technology has been divided into traditional manual survey collection technology and urban public transport data collection techonlogy based on modern information technology two parts.
Urban public transportation data warehouse and data mining technology and urban public transportation trip OD matrix inference are core and key. Based on public transportation IC card and GPS data sources, data warehouse structure system based on based on bus IC card and data warehouse structure system based on based on bus IC card and GPS data have been set up. And on this basis, the data mining structure system has been built including data warehouse module, data mining tool module, data logic analysis module and user control module four layers. Urban public transportation trip OD matrix inference has been divided into three parts including urban public transportation station OD matrix inference, urban public transportation trip OD matrix generation and urban public transportation trip OD matrix calibration. Among them, public transportation station OD matrix inference is the core content of the chapter, including public transport boarding station inference, public transportation alighting station inference and public transport transfer analysis and public transportation station OD matrix generation. The boarding station inference method is respectively cluster analysis method based on public transportation IC card data and scheduling information, time matching method based on public transportation IC card data and GPS data. And the alighting station inference method is respectively public transportation station attracting weight method, trip chain analysis method based on a single bus passenger.
Finally, the public transportation operation and planning decisions have been analyzed based on the mined information. There are three parts such as urban public transportation dynamic characteristics analysis, urban public transportation service quality analysis and urban public transportation trip characterstics analysis.
引文
[1]杜胜品,孔建益.城市交通拥挤与系统分担交通理论的应用[J],武汉科技大学学报(自然科学版),2004,27(1)：47-50.
[2]王丰元,陈荫三,宋年秀.交通需求管理及其在中国的应用[J],交通运输工程学报,2002,2(2)：83-87.
[3]新华网.温家宝曾培炎作批示要求优先发展城市公共交通[EB/OL]http://news.xinhuanet.com/politics/2005-10/31/content_3708176.htm.
[4]陈学武,戴霄,杨敏.先进的公交数据采集分析技术[J],会议论文,2005.
[5]陈茜,陈学武,王炜.城市智能公交中的信息采集与融合[J],城市公共交通,2003,5.
[6]Donghun Yoon.User Behavior Information and Diffusion Process for IC-Card System[J], JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY, VOL.1, NO.2, MAY 2010.
[7]王卓人,邓晋钧,刘宗祥.等编著.IC卡的技术与应用[M],电子工业出版社,1999.
[8]周李,李立明,刘建平.IC卡在城市公共交通中的应用研究[J],城市管理与科技,1999.2.
[9]Wonjae Jang. Travel Time and Transfer Analysis Using Transit Smart Card Data[J],TRB 2010 Annual Meeting CD-ROM.
[10]Fabio Gordillo. The Value of Automated Fare Collection Data for Transit Planning: An Example of Rail Transit OD Matrix EstimationfD], Massachusetts Institute of Technology.2006.
[11]Joanne Chan. Rail Transit OD Matrix Estimation and Journey Time Reliability Metrics Using Automated Fare Data[D],Massachusetts Institute of Technology,2007.
[12]田苗苗,周磊山,孙琦.北京市政公交一卡通使用现状及改进策略研究[J],城市公共交通,2007.(4)：22-26.
[13]新加坡实现银行卡和交通卡双卡合一[J],中国防伪报道,2009,(10)：61.
[14]Stiller, R., Ehrlich, T., Sutter, C. IMPACT OF THE IMPLEMENTATION OF THE NEW YORK METROPOLITAN TRANSPORTATION AUTHORITY'S METROCARD ON RIDERSHIP AND REVENUE OF THE WESTCHESTER COUNTY (NY) BEE-LINE BUS SYSTEM[C], TRB 2009 Annual Meeting CD-ROM.
[15]戴霄.丛于公交Ic信息的公交数据分析方法研究[D],东南大学硕士学位论文,2006.
[16]中国信息产业商会智能卡专业委员会.中国IC卡应用的现状及发展趋势[EB/OL]http://www.smartcard.org.cn/datel/page1000.html.
[17]吴名.上海市公共交通一卡通的现状与发展[J],金卡工程,2007,(12)：36-39.
[18]Martin Trepanier,Catherine Morency,Carl Blanchette. Enhancing household travel surveys using smart card data?[C],TRB 2009 Annual Meeting CD-ROM.
[19]Ka Kee Alfred CHU,Robert CHAPLEAU,Martin TREPANIER.Driver-Assisted Bus Interview (DABI):Passive Transit Travel Survey using Smart Card Automatic Fare Collection System and its Applications[C],TRB 2009 Annual Meeting CD-ROM.
[20]陈学武,戴霄,陈茜.公交IC卡信息采集、分析与应用研究[J],上木工程学报,2004,37(2)：105-110.
[21]陈学武,戴霄,杨敏.先进的公交出行数据采集分析方法[C],2005年海峡两岸智能交通运输系统学术研讨会暨第二届同舟交通论坛,上海：同济大学出版社,2005,595-603.
[22]宗芳,贾洪飞,王涛,张慧永.基于IC卡的公交出行数据调查方法研究[C],城市公共交通学会研讨会论文集,2007,12-19.
[23]姚宝珍,于艳弘,于滨.公交IC卡收费系统与客流数据采集、处理[J].长春工业大学学报(自然科学版),2005,26(3)：239-241.
[24]赵晖.基于公交IC卡信息的居民出行OD推算研究[D],长安大学硕士学位论文,2009.
[25]杨盛华.基于现代信息技术的公交客流数据采集方法及应用研究[D],吉林大学硕士学位论文,2009.
[26]师富民.基于IC卡数据的公交OD矩阵构造方法研究[D],吉林大学硕士学位论文,2004.
[27]冯艳春.基于IC卡数据的公交规划方法研究[D],吉林大学硕士学位论文,2005.
[28]李鸿艳.公交IC卡分段收费的实现[J],交通信息与安全,2010,29(2)：98-100.
[29]路智宁.对IC卡交易数据的挖掘和分析[D],广东工业大学硕士学位论文,2005.
[30]孙旭.公交IC卡数据分析和数据仓库构建研究[D],吉林大学硕士学位论文,2008.
[31]袁勇.公交IC卡数据挖掘技术及应用研究[D],吉林大学硕士学位论文,2009.
[32]章玉.基于数据挖掘的动态公交客流00获取方法研究[D],北京交通大学硕士学位论文,2010.
[33]周崇华.基于IC卡数据的深圳地铁OD信息处理技术[J],城市轨道交通研究,2007,10(1)：54-56.
[34]查伟雄,刘金行.公交站点IC刷卡计数算法及其Matlab实现[J],交通信息与安全,2010,28(2)：93-97.
[35]Barry James J., Freimer Robert, Slavin Howard. Use of entry-only automatic fare collection data to estimate linked transit trips in New York city[J], Transportation Research Record, n 2112, p 53-61,2009.
[36]Zhang Lianfu, Zhao Shuzhi, Zhu Yonggang, Zhu Ziyin. Study on the Method of Constructing Bus Stops OD Matrix Based on IC Card Data[C],International Conference on Wireless Communications, Networking and Mobile Computing, WiCom 2007.
[37]杨秀华.基于准实时客流信息的公交调度优化研究[D],吉林大学硕士学位论文,2008.
[38]尹长勇,陈艳艳,陈绍辉.基于聚类分析方法的公交站点客流匹配方法研究[J],交通信 息与安全,2010,28(3)：21-24.
[39]于勇,邓天民,肖裕民.一种新的公交乘客上车站点确定方法[J],重庆交通大学学报(自然科学版),2009,28(1)：121-125.
[40]戴霄,陈学武.单条公交线路的IC卡数据分析处理方法[J],城市交通,2005,3(4)：73-76.
[41]舒国辉.基于数据挖掘的公家客流规律研究[D],北京交通大学硕士学位论文,2009.
[42]郭婕.公交IC卡通勤乘客OD确定方法研究[D],东南大学硕十学位论文,2006.
[43]郭婕,陈学武.公交IC卡乘客上车站点确定方法及其应用[C],第一届中国智能交通年会论文集,上海：同济大学出版社,2005,755-759.
[44]Alex Cui. Bus passenger Origin-Destination Matrix estimation using Automated Data Collection systems[D],Massachusetts Institute of Technology,2006.
[45]Janine M. Farzin. Constructing an Automated Bus Origin-Destination Matrix Using Farecard and Global Positioning System Data in Sao Paulo, Brazil[J],Transportation Research Record: Journal of the Transportation Research Board.No.2072, Transportation Research Board of the National Academies, Washington,D.C.,2008, pp.30-37.
[46]章威,徐建闽.基于GPS与IC卡的公交OD量采集方法[J],交通与计算机,2006,24(2)：21-23.
[47]徐建闽,熊文华,游峰.基于GPS和IC卡的单线公交OD生成方法[J],微计算机信息,2008,24(22)：221-223.
[48]刘颖杰,靳文舟,康凯.基于IC信息和概率理论的公交OD反推方法[J],公路与汽运,2010, (3)： 31-33.
[49]周涛,翟长旭,高志刚.基于公交1C卡数据的OD推算技术研究[J],城市交通,2007,5(3)：49-52.
[50]孙文.IC卡公交乘车数据库OD矩阵的构造研究[D],山东大学硕士学位论文,2007.
[51]戴霄,陈学武,李文勇.公交IC卡信息处理的数据挖掘技术研究[J],交通与计算机,2006,24(1)：40-42.
[52]陈学武,戴霄.公交IC卡持卡乘客下车站点确定方法研究[C],第三届中国智能交通年会论文集,南京：东南大学出版社,2007,73-77.
[53]朱丽云,陈锋,高永,邓小勇.丛于GIS的公交IC卡客流信息采集与分析系统研究[C].第三届中国国际数字城市建设技术研讨会论文集,北京：中国城市出版社,2007,594-597.
[54]Barry James J., Newhouser Robert, Rahbee Adam, Sayeda Shermeen. Origin and destination estimation in New York City with automated fare system data[J], Transportation Research Record, n 1817, p 183-187,2002.
[55]Jinhua Zhao. The Planning and Analysis Implications of Automated Data Collection Systems: Rail Transit OD Matrix Inference and Path Choice Modeling Examples[D],Massachusetts Institute of Technology.2004.
[56]高永,邓小勇.基于IC卡数据的公交换乘识别方法[C],第三届中国智能交通年会论文集,南京：东南大学出版社,2007,123-127.
[57]彭晗,韩秀华,田振中,秦朝举.公交IC卡数据处理的换乘矩阵构造方法研究[J],交通与计算机,2007,25(4)：32-34.
[58]董晓晶,余志伟,伏伟伟,孙影,陈静.基于GIS的公交IC卡数据处理及分析系统[J],地理空间信息,2009,7(5)：124-126.
[59]Catherine Seaborn, Nigel H.M. Wilson, John Attanucci. Using Smart Card Fare Payment Data To Analyze Multi-Modal Public Transport Journeys (London, UK) [C], TRB 2009 Annual Meeting CD-ROM.
[60]Markus Hofmann, Margaret O'Mahony. Transfer Journey Identification and Analyses from Electronic Fare Collection Data[C], Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems Vienna, Austria, September 13-16,2005.
[61]Markus Hofmann, Simon Wilson, Peter White. Automated Identification of Linked Trips at Trip Level Using Electronic Fare Collection Data[C], TRB 2009 Annual Meeting CD-ROM.
[62]Yanyan CHEN, Shaohui CHEN, Changyong YIN, Wentao LIU, Zhihong CHEN, and Jingjing WANG. Analysis Public Transport Performance Based on IC Data[C],ICCTP 2010:Integrated Transportation Systems-Green ·Intelligent·Reliable.
[63]韩秀华,李津,郑黎黎.基于IC卡信息的居民公交出行动态特性[J],吉林大学学报(工学版),2009,39(增刊)：124-128.
[64]Zhu Qing, Wang Yingzhe, Li Jiankou. Public Transport IC Card Data Analysis and Operation Strategy Research Based on Data Mining Technology[C],2009 International Forum on Computer Science-Technology and Applications.
[65]杨智伟,赵骞,赵胜川,金雷,毛羿.基于公交IC卡数据信息的客流预测方法研究[J],交通标准化,2009,(196)：115-119.
[66]徐立泉.IC卡客流信息在公共交通运营管理中的应用研究[D],北京工业大学硕士学位论文,2005.
[67]LIU Jianfeng, LI Jinhai, CHEN Feng, ZHOU Yanqiu. Review on Station-to-station OD Matrix Estimation Model and Algorithm for Urban Rail Transit[C],2010 Second International Conference on Computer Modeling and Simulation.
[68]赵骞.基于公交IC卡调查数据的公交调度优化研究[D],大连理工大学硕士学位论文,2007.
[69]朱永刚.城市公交线网优化方法CVO法及其应用研究[D],吉林大学硕上学位论文,2007.
[70]Alla Reddy, Alex Lu, Santosh Kumar, Victor Bashmakov, and Svetlana Rudenko. Entry-Only Automated Fare-Collection System Data Used to Infer Ridership, Rider Destinations, Unlinked Trips, and Passenger Miles[J], Transportation Research Record:Journal of the Transportation Research Board,n2110, p128-136,2009.
[71]David L. Uniman, John Attanucci, Rabi G. Mishalani, Nigel H. M. Wilson. Service Reliability Measurement using Automated Fare Card Data: Application to the London Underground[C], TRB 2010 Annual Meeting CD-ROM.
[72]Ka Kee Alfred CHU,Robert CHAPLEAU.Augmenting Transit Trip Characterization and Travel Behavior Comprehension with Multi-day Location-Stamped Smart Card Transactions[C],TRB 2010 Annual Meeting CD-ROM.
[73]陈京民等编著.数据仓库与数据挖掘技术[M],电子工业出版社,2002.
[74]陈文伟等编著.数据仓库与数据挖掘教程[M],清华大学出版社,2006.
[75]郭淑霞.基于时变二源数据的城市公交调度协调模型与算法[D],北京交通大学博士学位论文,2010.
[2]王丰元,陈荫三,宋年秀.交通需求管理及其在中国的应用[J],交通运输工程学报,2002,2(2)：83-87.
[3]新华网.温家宝曾培炎作批示要求优先发展城市公共交通[EB/OL]http://news.xinhuanet.com/politics/2005-10/31/content_3708176.htm.
[4]陈学武,戴霄,杨敏.先进的公交数据采集分析技术[J],会议论文,2005.
[5]陈茜,陈学武,王炜.城市智能公交中的信息采集与融合[J],城市公共交通,2003,5.
[6]Donghun Yoon.User Behavior Information and Diffusion Process for IC-Card System[J], JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY, VOL.1, NO.2, MAY 2010.
[7]王卓人,邓晋钧,刘宗祥.等编著.IC卡的技术与应用[M],电子工业出版社,1999.
[8]周李,李立明,刘建平.IC卡在城市公共交通中的应用研究[J],城市管理与科技,1999.2.
[9]Wonjae Jang. Travel Time and Transfer Analysis Using Transit Smart Card Data[J],TRB 2010 Annual Meeting CD-ROM.
[10]Fabio Gordillo. The Value of Automated Fare Collection Data for Transit Planning: An Example of Rail Transit OD Matrix EstimationfD], Massachusetts Institute of Technology.2006.
[11]Joanne Chan. Rail Transit OD Matrix Estimation and Journey Time Reliability Metrics Using Automated Fare Data[D],Massachusetts Institute of Technology,2007.
[12]田苗苗,周磊山,孙琦.北京市政公交一卡通使用现状及改进策略研究[J],城市公共交通,2007.(4)：22-26.
[13]新加坡实现银行卡和交通卡双卡合一[J],中国防伪报道,2009,(10)：61.
[14]Stiller, R., Ehrlich, T., Sutter, C. IMPACT OF THE IMPLEMENTATION OF THE NEW YORK METROPOLITAN TRANSPORTATION AUTHORITY'S METROCARD ON RIDERSHIP AND REVENUE OF THE WESTCHESTER COUNTY (NY) BEE-LINE BUS SYSTEM[C], TRB 2009 Annual Meeting CD-ROM.
[15]戴霄.丛于公交Ic信息的公交数据分析方法研究[D],东南大学硕士学位论文,2006.
[16]中国信息产业商会智能卡专业委员会.中国IC卡应用的现状及发展趋势[EB/OL]http://www.smartcard.org.cn/datel/page1000.html.
[17]吴名.上海市公共交通一卡通的现状与发展[J],金卡工程,2007,(12)：36-39.
[18]Martin Trepanier,Catherine Morency,Carl Blanchette. Enhancing household travel surveys using smart card data?[C],TRB 2009 Annual Meeting CD-ROM.
[19]Ka Kee Alfred CHU,Robert CHAPLEAU,Martin TREPANIER.Driver-Assisted Bus Interview (DABI):Passive Transit Travel Survey using Smart Card Automatic Fare Collection System and its Applications[C],TRB 2009 Annual Meeting CD-ROM.
[20]陈学武,戴霄,陈茜.公交IC卡信息采集、分析与应用研究[J],上木工程学报,2004,37(2)：105-110.
[21]陈学武,戴霄,杨敏.先进的公交出行数据采集分析方法[C],2005年海峡两岸智能交通运输系统学术研讨会暨第二届同舟交通论坛,上海：同济大学出版社,2005,595-603.
[22]宗芳,贾洪飞,王涛,张慧永.基于IC卡的公交出行数据调查方法研究[C],城市公共交通学会研讨会论文集,2007,12-19.
[23]姚宝珍,于艳弘,于滨.公交IC卡收费系统与客流数据采集、处理[J].长春工业大学学报(自然科学版),2005,26(3)：239-241.
[24]赵晖.基于公交IC卡信息的居民出行OD推算研究[D],长安大学硕士学位论文,2009.
[25]杨盛华.基于现代信息技术的公交客流数据采集方法及应用研究[D],吉林大学硕士学位论文,2009.
[26]师富民.基于IC卡数据的公交OD矩阵构造方法研究[D],吉林大学硕士学位论文,2004.
[27]冯艳春.基于IC卡数据的公交规划方法研究[D],吉林大学硕士学位论文,2005.
[28]李鸿艳.公交IC卡分段收费的实现[J],交通信息与安全,2010,29(2)：98-100.
[29]路智宁.对IC卡交易数据的挖掘和分析[D],广东工业大学硕士学位论文,2005.
[30]孙旭.公交IC卡数据分析和数据仓库构建研究[D],吉林大学硕士学位论文,2008.
[31]袁勇.公交IC卡数据挖掘技术及应用研究[D],吉林大学硕士学位论文,2009.
[32]章玉.基于数据挖掘的动态公交客流00获取方法研究[D],北京交通大学硕士学位论文,2010.
[33]周崇华.基于IC卡数据的深圳地铁OD信息处理技术[J],城市轨道交通研究,2007,10(1)：54-56.
[34]查伟雄,刘金行.公交站点IC刷卡计数算法及其Matlab实现[J],交通信息与安全,2010,28(2)：93-97.
[35]Barry James J., Freimer Robert, Slavin Howard. Use of entry-only automatic fare collection data to estimate linked transit trips in New York city[J], Transportation Research Record, n 2112, p 53-61,2009.
[36]Zhang Lianfu, Zhao Shuzhi, Zhu Yonggang, Zhu Ziyin. Study on the Method of Constructing Bus Stops OD Matrix Based on IC Card Data[C],International Conference on Wireless Communications, Networking and Mobile Computing, WiCom 2007.
[37]杨秀华.基于准实时客流信息的公交调度优化研究[D],吉林大学硕士学位论文,2008.
[38]尹长勇,陈艳艳,陈绍辉.基于聚类分析方法的公交站点客流匹配方法研究[J],交通信 息与安全,2010,28(3)：21-24.
[39]于勇,邓天民,肖裕民.一种新的公交乘客上车站点确定方法[J],重庆交通大学学报(自然科学版),2009,28(1)：121-125.
[40]戴霄,陈学武.单条公交线路的IC卡数据分析处理方法[J],城市交通,2005,3(4)：73-76.
[41]舒国辉.基于数据挖掘的公家客流规律研究[D],北京交通大学硕士学位论文,2009.
[42]郭婕.公交IC卡通勤乘客OD确定方法研究[D],东南大学硕十学位论文,2006.
[43]郭婕,陈学武.公交IC卡乘客上车站点确定方法及其应用[C],第一届中国智能交通年会论文集,上海：同济大学出版社,2005,755-759.
[44]Alex Cui. Bus passenger Origin-Destination Matrix estimation using Automated Data Collection systems[D],Massachusetts Institute of Technology,2006.
[45]Janine M. Farzin. Constructing an Automated Bus Origin-Destination Matrix Using Farecard and Global Positioning System Data in Sao Paulo, Brazil[J],Transportation Research Record: Journal of the Transportation Research Board.No.2072, Transportation Research Board of the National Academies, Washington,D.C.,2008, pp.30-37.
[46]章威,徐建闽.基于GPS与IC卡的公交OD量采集方法[J],交通与计算机,2006,24(2)：21-23.
[47]徐建闽,熊文华,游峰.基于GPS和IC卡的单线公交OD生成方法[J],微计算机信息,2008,24(22)：221-223.
[48]刘颖杰,靳文舟,康凯.基于IC信息和概率理论的公交OD反推方法[J],公路与汽运,2010, (3)： 31-33.
[49]周涛,翟长旭,高志刚.基于公交1C卡数据的OD推算技术研究[J],城市交通,2007,5(3)：49-52.
[50]孙文.IC卡公交乘车数据库OD矩阵的构造研究[D],山东大学硕士学位论文,2007.
[51]戴霄,陈学武,李文勇.公交IC卡信息处理的数据挖掘技术研究[J],交通与计算机,2006,24(1)：40-42.
[52]陈学武,戴霄.公交IC卡持卡乘客下车站点确定方法研究[C],第三届中国智能交通年会论文集,南京：东南大学出版社,2007,73-77.
[53]朱丽云,陈锋,高永,邓小勇.丛于GIS的公交IC卡客流信息采集与分析系统研究[C].第三届中国国际数字城市建设技术研讨会论文集,北京：中国城市出版社,2007,594-597.
[54]Barry James J., Newhouser Robert, Rahbee Adam, Sayeda Shermeen. Origin and destination estimation in New York City with automated fare system data[J], Transportation Research Record, n 1817, p 183-187,2002.
[55]Jinhua Zhao. The Planning and Analysis Implications of Automated Data Collection Systems: Rail Transit OD Matrix Inference and Path Choice Modeling Examples[D],Massachusetts Institute of Technology.2004.
[56]高永,邓小勇.基于IC卡数据的公交换乘识别方法[C],第三届中国智能交通年会论文集,南京：东南大学出版社,2007,123-127.
[57]彭晗,韩秀华,田振中,秦朝举.公交IC卡数据处理的换乘矩阵构造方法研究[J],交通与计算机,2007,25(4)：32-34.
[58]董晓晶,余志伟,伏伟伟,孙影,陈静.基于GIS的公交IC卡数据处理及分析系统[J],地理空间信息,2009,7(5)：124-126.
[59]Catherine Seaborn, Nigel H.M. Wilson, John Attanucci. Using Smart Card Fare Payment Data To Analyze Multi-Modal Public Transport Journeys (London, UK) [C], TRB 2009 Annual Meeting CD-ROM.
[60]Markus Hofmann, Margaret O'Mahony. Transfer Journey Identification and Analyses from Electronic Fare Collection Data[C], Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems Vienna, Austria, September 13-16,2005.
[61]Markus Hofmann, Simon Wilson, Peter White. Automated Identification of Linked Trips at Trip Level Using Electronic Fare Collection Data[C], TRB 2009 Annual Meeting CD-ROM.
[62]Yanyan CHEN, Shaohui CHEN, Changyong YIN, Wentao LIU, Zhihong CHEN, and Jingjing WANG. Analysis Public Transport Performance Based on IC Data[C],ICCTP 2010:Integrated Transportation Systems-Green ·Intelligent·Reliable.
[63]韩秀华,李津,郑黎黎.基于IC卡信息的居民公交出行动态特性[J],吉林大学学报(工学版),2009,39(增刊)：124-128.
[64]Zhu Qing, Wang Yingzhe, Li Jiankou. Public Transport IC Card Data Analysis and Operation Strategy Research Based on Data Mining Technology[C],2009 International Forum on Computer Science-Technology and Applications.
[65]杨智伟,赵骞,赵胜川,金雷,毛羿.基于公交IC卡数据信息的客流预测方法研究[J],交通标准化,2009,(196)：115-119.
[66]徐立泉.IC卡客流信息在公共交通运营管理中的应用研究[D],北京工业大学硕士学位论文,2005.
[67]LIU Jianfeng, LI Jinhai, CHEN Feng, ZHOU Yanqiu. Review on Station-to-station OD Matrix Estimation Model and Algorithm for Urban Rail Transit[C],2010 Second International Conference on Computer Modeling and Simulation.
[68]赵骞.基于公交IC卡调查数据的公交调度优化研究[D],大连理工大学硕士学位论文,2007.
[69]朱永刚.城市公交线网优化方法CVO法及其应用研究[D],吉林大学硕上学位论文,2007.
[70]Alla Reddy, Alex Lu, Santosh Kumar, Victor Bashmakov, and Svetlana Rudenko. Entry-Only Automated Fare-Collection System Data Used to Infer Ridership, Rider Destinations, Unlinked Trips, and Passenger Miles[J], Transportation Research Record:Journal of the Transportation Research Board,n2110, p128-136,2009.
[71]David L. Uniman, John Attanucci, Rabi G. Mishalani, Nigel H. M. Wilson. Service Reliability Measurement using Automated Fare Card Data: Application to the London Underground[C], TRB 2010 Annual Meeting CD-ROM.
[72]Ka Kee Alfred CHU,Robert CHAPLEAU.Augmenting Transit Trip Characterization and Travel Behavior Comprehension with Multi-day Location-Stamped Smart Card Transactions[C],TRB 2010 Annual Meeting CD-ROM.
[73]陈京民等编著.数据仓库与数据挖掘技术[M],电子工业出版社,2002.
[74]陈文伟等编著.数据仓库与数据挖掘教程[M],清华大学出版社,2006.
[75]郭淑霞.基于时变二源数据的城市公交调度协调模型与算法[D],北京交通大学博士学位论文,2010.