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居民公交出行链重复性量化分析及其出行规律研究

崔洪军 孙婉茹 赵锐 朱敏清 李霞

崔洪军, 孙婉茹, 赵锐, 朱敏清, 李霞. 居民公交出行链重复性量化分析及其出行规律研究[J]. 交通信息与安全, 2021, 39(3): 128-135. doi: 10.3963/j.jssn.1674-4861.2021.03.016
引用本文: 崔洪军, 孙婉茹, 赵锐, 朱敏清, 李霞. 居民公交出行链重复性量化分析及其出行规律研究[J]. 交通信息与安全, 2021, 39(3): 128-135. doi: 10.3963/j.jssn.1674-4861.2021.03.016
CUI Hongjun, SUN Wanru, ZHAO Rui, ZHU Minqing, LI Xia. A Quantitative Analysis on Repeatability of Residents'Bus Trip Chain and Travel Regularity[J]. Journal of Transport Information and Safety, 2021, 39(3): 128-135. doi: 10.3963/j.jssn.1674-4861.2021.03.016
Citation: CUI Hongjun, SUN Wanru, ZHAO Rui, ZHU Minqing, LI Xia. A Quantitative Analysis on Repeatability of Residents'Bus Trip Chain and Travel Regularity[J]. Journal of Transport Information and Safety, 2021, 39(3): 128-135. doi: 10.3963/j.jssn.1674-4861.2021.03.016

居民公交出行链重复性量化分析及其出行规律研究

doi: 10.3963/j.jssn.1674-4861.2021.03.016
基金项目: 

国家自然科学基金项目 51678212

河北省科技厅专项 19970808D

详细信息
    通讯作者:

    崔洪军(1974—),博士,教授.研究方向:交通规划与管理、交通安全.E-mail:cuihj1974@126.com

  • 中图分类号: U491.1

A Quantitative Analysis on Repeatability of Residents'Bus Trip Chain and Travel Regularity

  • 摘要: 作为城市交通的枢纽,公共交通系统承载了大量的居民出行。自动数据采集系统收集的IC卡数据包含了大量的乘客出行信息,通过这些数据可分析居民公交出行规律,进而优化公交服务。引入信息熵及熵率对居民公交出行链重复性进行量化,研究了基于量化指标分析居民公交出行规律的方法。通过出行地点状态标定,将乘客的出行链转化为离散的出行序列;利用信息熵和熵率对出行序列进行量化分析,得到出行重复性与量化指标的关系,即出行序列的信息熵越大,熵率越小,该乘客出行重复性越高,出行规律越强。基于重复性量化处理,以石家庄公交智能卡乘客出行数据为例,分别从群体和个人这2个方面对公交乘客的出行规律进行分析。结果表明,出行链重复性量化指标可以对出行规律的强弱进行直观判断。当乘客出行规律不明显,但信息熵高于样本均值2.53 bits、熵率低于样本均值1.13 bits/事件时,可通过进一步分析挖掘出乘客潜在出行规律。

     

  • 图  1  公交出行链时空关联特征示意图

    Figure  1.  Temporal-spatial correlation features of the bus-trip chain

    图  2  智能卡乘客出行序列的信息熵分布

    Figure  2.  Distribution of entropy across passengers using smart cards

    图  3  智能卡乘客出行序列熵率分布

    Figure  3.  Distribution of the entropy rates across smart card passengers

    图  4  所选乘客出行重复性量化指标散点图

    Figure  4.  Scatter of the quantitative indicators of the repeatability of the selected passengers

    图  5  所选卡号为A的乘客出行活动序列

    Figure  5.  Activity sequence of CardholderA

    图  6  所选卡号为B的乘客出行活动序列

    Figure  6.  Activity sequence of CardholderB

    图  7  所选卡号为C的乘客出行活动序列

    Figure  7.  Activity sequence of CardholderC

    表  1  持卡人出行记录

    Table  1.   Cardholder's travel records

    交易时间 线路名 站点名称
    2018-01-01 6:31 2路 北国商城
    2018-01-01 10:22 2路 胸科医院
    2018-01-02 6:54 2路 北国商城
    2018-01-02 10:26 2路 胸科医院
    2018-01-03 6:31 2路 水务集团
    2018-01-03 6:49 2路 北国商城
    2018-01-03 10:49 2路 胸科医院
    2018-01-04 15:05 2路 北国商城
    2018-01-06 06:25 2路 市城管委
    2018-01-06 10:25 2路 水务集团
    2018-01-06 11:08 27路 老年病医院
    下载: 导出CSV

    表  2  所选乘客出行重复性量化指标统计

    Table  2.   Quantitative indicators of the repeatability of selected passengers'travel

    乘客群体
    (样本量)
    总样本
    (600)
    老年卡
    (200)
    成人卡
    (200)
    学生卡
    (200)
    信息熵H(X) 2.509 2.379 2.539 2.610
    熵率H '(X) 1.132 1.199 1.113 1.086
    下载: 导出CSV

    表  3  所选乘客出行重复性度量指标统计

    Table  3.   Quantitative indicators of the repeatability of selected passengers'travel

    乘客卡号 A B C
    信息熵H(X) 2.636 2.512 2.343
    熵率H '(X) 1.073 1.124 1.165
    下载: 导出CSV
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  • 收稿日期:  2020-06-16

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