作者利用公交刷卡数据(Smart Card Data,SCD)和兴趣点(Point of Interest,POI)数据,借助Oracle数据库和地理信息系统对城市街区层面的功能属性识别进行了研究。其中SCD用于刻画街区客流特征的功能属性,POI。数据用于刻画街区设施功能属...作者利用公交刷卡数据(Smart Card Data,SCD)和兴趣点(Point of Interest,POI)数据,借助Oracle数据库和地理信息系统对城市街区层面的功能属性识别进行了研究。其中SCD用于刻画街区客流特征的功能属性,POI。数据用于刻画街区设施功能属性。作者首先利用公交站点客流出行规律的功能属性对城市街区进行初步的分类。在此基础之上,利用POI数据的设施功能属性字段进行蚁群聚类,对城市功能进行进一步细分和识别。最后利用遥感影像分析对识别结果进行检验。检验结果表明,综合利用公交刷卡数据和兴趣点数据能较为准确刻画城市街区的功能特征。展开更多
基于位置服务(Location Based Service,LBS)技术为研究城市系统的时空动态规律提供了新的视角,已往多基于移动通讯(GSM)、全球定位系统(GPS)、社会化网络(SNS)和无线宽带热点(Wi-Fi)数据开展研究,但少有研究利用公交IC卡刷卡数据进行城...基于位置服务(Location Based Service,LBS)技术为研究城市系统的时空动态规律提供了新的视角,已往多基于移动通讯(GSM)、全球定位系统(GPS)、社会化网络(SNS)和无线宽带热点(Wi-Fi)数据开展研究,但少有研究利用公交IC卡刷卡数据进行城市系统分析。普遍存在的LBS数据虽然具有丰富的时间和空间信息,但缺乏社会维度信息,使其应用范围受到一定限制。本文基于2008年北京市连续一周的公交IC卡(Smart Card Data,SCD)刷卡数据,结合2005年居民出行调查、地块级别的土地利用图,识别公交持卡人的居住地、就业地和通勤出行,并将识别结果在公交站点和交通分析小区(TAZ)尺度上汇总:①将识别的通勤出行分别从通勤时间和距离角度,与居民出行调查数据和其他已有北京相关研究进行对比,显示较好的吻合性;②对来自3大典型居住区和去往6大典型办公区的通勤出行进行可视化并对比分析;③对全市基于公交的通勤出行进行可视化,并识别主要交通流方向。本研究初步提出了从传统的居民出行调查和城市GIS数据建立规则,用于SCD数据挖掘的方法,具有较好的可靠性。展开更多
As an essential component of bus dwelling time, passenger boarding time has a significant impact on bus running reliability and service quality. In order to understand the passengers’ boarding process and mitigate pa...As an essential component of bus dwelling time, passenger boarding time has a significant impact on bus running reliability and service quality. In order to understand the passengers’ boarding process and mitigate passenger boarding time, a regression analysis framework is proposed to capture the difference and influential factors of boarding time for adult and elderly passengers based on smart card data from Changzhou. Boarding gap, the time difference between two consecutive smart card tapping records, is calculated to approximate passenger boarding time. Analysis of variance is applied to identify whether the difference in boarding time between adults and seniors is statistically significant. The multivariate regression modeling approach is implemented to analyze the influences of passenger types, marginal effects of each additional boarding passenger and bus floor types on the total boarding time at each stop. Results show that a constant difference exists in boarding time between adults and seniors even without considering the specific bus characteristics. The average passenger boarding time decreases when the number of passenger increases. The existence of two entrance steps delays the boarding process, especially for elderly passengers.展开更多
文摘作者利用公交刷卡数据(Smart Card Data,SCD)和兴趣点(Point of Interest,POI)数据,借助Oracle数据库和地理信息系统对城市街区层面的功能属性识别进行了研究。其中SCD用于刻画街区客流特征的功能属性,POI。数据用于刻画街区设施功能属性。作者首先利用公交站点客流出行规律的功能属性对城市街区进行初步的分类。在此基础之上,利用POI数据的设施功能属性字段进行蚁群聚类,对城市功能进行进一步细分和识别。最后利用遥感影像分析对识别结果进行检验。检验结果表明,综合利用公交刷卡数据和兴趣点数据能较为准确刻画城市街区的功能特征。
文摘基于位置服务(Location Based Service,LBS)技术为研究城市系统的时空动态规律提供了新的视角,已往多基于移动通讯(GSM)、全球定位系统(GPS)、社会化网络(SNS)和无线宽带热点(Wi-Fi)数据开展研究,但少有研究利用公交IC卡刷卡数据进行城市系统分析。普遍存在的LBS数据虽然具有丰富的时间和空间信息,但缺乏社会维度信息,使其应用范围受到一定限制。本文基于2008年北京市连续一周的公交IC卡(Smart Card Data,SCD)刷卡数据,结合2005年居民出行调查、地块级别的土地利用图,识别公交持卡人的居住地、就业地和通勤出行,并将识别结果在公交站点和交通分析小区(TAZ)尺度上汇总:①将识别的通勤出行分别从通勤时间和距离角度,与居民出行调查数据和其他已有北京相关研究进行对比,显示较好的吻合性;②对来自3大典型居住区和去往6大典型办公区的通勤出行进行可视化并对比分析;③对全市基于公交的通勤出行进行可视化,并识别主要交通流方向。本研究初步提出了从传统的居民出行调查和城市GIS数据建立规则,用于SCD数据挖掘的方法,具有较好的可靠性。
基金The National Natural Science Foundation of China(No.51338003,71801041)
文摘As an essential component of bus dwelling time, passenger boarding time has a significant impact on bus running reliability and service quality. In order to understand the passengers’ boarding process and mitigate passenger boarding time, a regression analysis framework is proposed to capture the difference and influential factors of boarding time for adult and elderly passengers based on smart card data from Changzhou. Boarding gap, the time difference between two consecutive smart card tapping records, is calculated to approximate passenger boarding time. Analysis of variance is applied to identify whether the difference in boarding time between adults and seniors is statistically significant. The multivariate regression modeling approach is implemented to analyze the influences of passenger types, marginal effects of each additional boarding passenger and bus floor types on the total boarding time at each stop. Results show that a constant difference exists in boarding time between adults and seniors even without considering the specific bus characteristics. The average passenger boarding time decreases when the number of passenger increases. The existence of two entrance steps delays the boarding process, especially for elderly passengers.
