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基于多源数据的公交出行特征分析 被引量:3

Analysis of Bus Trip Characteristics Based on Multi-source Data
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摘要 为准确分析公交消费数据不完整情况下的公交出行特征,基于乘客上车刷卡数据、支付宝扫码数据及公交GPS数据,运用时空匹配法和出行链理论挖掘分析乘客上下车站点、公交线路OD矩阵、出行空间分布特性及消费时间分布特征。实际验证结果表明:1)使用IC卡和支付宝的乘客数量近似相等,使用现金人数较少,约占整体的6%;2)乘客出行次数在2次以下占总数的84%,换乘需求较少,公交可达性较高;3)高峰期消费次数均超过25000次/h,约占全天总数的23%,居民出行目的较为单一,大部分往返于居民区与办公商业区,与实际情况相符。 In order to accurately analyze the characteristics of bus travel under the condition of incomplete bus consumption data,this paper analyzes passenger pick-up and drop-off stations,bus lines OD matrix,spatial distribution characteristics of travel space and consumption time distribution characteristics by timespace matching method and trip chain theory based on passengers’card swiping data,Alipay scan code data and bus GPS data.The results show that the number of passengers using IC card is approximately equal to that of using Alipay,and that of using cash is small,accounting for about 6%of the total;the number of passengers travel less than 2 times accounted for 84%of the total with fewer transfer needs and higher bus accessibility;peak consumption times are more than 25,000 times per hour,accounting for about 23%of the total throughout the day.The purpose of residents’travel is relatively single,most of them travel between residential areas and office and commercial areas,which is in consistent with the actual situation.
作者 杨昊 霍晓艳 赵林涛 冷军强 白昊鹏 YANG Hao;HUO Xiaoyan;ZHAO Lintao;LENG Junqiang;BAI Haopeng(School of Transportation Science and Engineering,Harbin Institute of Technology,Harbin,150090,Heilongjiang,China;School of Automotive Engineering,Harbin Institute of Technology(Weihai),Weihai,264209,Shandong,China;Imperial College London,London,UK)
出处 《公路交通技术》 2020年第2期132-137,144,共7页 Technology of Highway and Transport
基金 山东省重点研发计划项目(2017GGX50113)。
关键词 多源数据 出行特征 数据挖掘 出行链 OD矩阵 multi-source data travel characteristics data mining trip chain OD(origin-destination)matrix
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