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考虑潜在类别的市内机动化出行行为模型

刘志伟 刘建荣 邓卫

刘志伟, 刘建荣, 邓卫. 考虑潜在类别的市内机动化出行行为模型[J]. 西南交通大学学报, 2021, 56(1): 131-137. doi: 10.3969/j.issn.0258-2724.20190945
引用本文: 刘志伟, 刘建荣, 邓卫. 考虑潜在类别的市内机动化出行行为模型[J]. 西南交通大学学报, 2021, 56(1): 131-137. doi: 10.3969/j.issn.0258-2724.20190945
LIU Zhiwei, LIU Jianrong, DENG Wei. Inclusion of Latent Class in Behavior Model of Motorized Travel in City[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 131-137. doi: 10.3969/j.issn.0258-2724.20190945
Citation: LIU Zhiwei, LIU Jianrong, DENG Wei. Inclusion of Latent Class in Behavior Model of Motorized Travel in City[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 131-137. doi: 10.3969/j.issn.0258-2724.20190945

考虑潜在类别的市内机动化出行行为模型

doi: 10.3969/j.issn.0258-2724.20190945
基金项目: 国家自然科学基金(51578247)
详细信息
    作者简介:

    刘志伟(1987—),男,讲师,博士,研究方向为交通工程,E-mail:tonyliuzhiwei@whpu.edu.cn

    通讯作者:

    刘建荣(1984—),男,讲师,博士,研究方向为交通工程,E-mail:ctjrliu@scut.edu.cn

  • 中图分类号: U121

Inclusion of Latent Class in Behavior Model of Motorized Travel in City

  • 摘要: 为了研究出行者出行选择偏好的异质性和心理因素对出行选择行为的影响,通过验证性因子分析得到影响出行方式选择的心理潜变量;将求得的潜变量纳入潜在类别条件Logit模型,采用期望最大算法求解,得到样本潜在类别的数量和效用函数;最后,以广州市为例进行实证分析. 结果表明:潜在类别条件Logit模型对数据的拟合度高于传统的条件Logit模型;出行者可以划分为地铁偏好群体、小汽车偏好群体、常规公交偏好群体3个潜在类别,占比分别为42.5%、25.0%、32.5%;地铁偏好群体、公交偏好群体步行时间价值分别为1.2、1.3元/min,而小汽车偏好群体对步行持正面评价;地铁偏好群体、公交偏好群体的时间价值均为0.7元/min,小于小汽车偏好群体的车内时间价值(1.1元/min);月收入是否大于10 000元、是否开车上班对出行者潜在类别划分具有显著影响;心理潜变量中,灵活性和可靠性对出行者潜在类别划分的影响显著,舒适性对潜在类别划分没有显著影响.

     

  • 图 1  月收入及是否使用小汽车通勤对潜在类别的影响

    Figure 1.  Impacts of monthly income and choosing whether to use car for commuting on latent class

    表  1  SP情景示例

    Table  1.   Example of SP choice scenario

    出行方式费用/元时间/min
    小汽车油价 + 停车费:14.0开车时间:10
    公交车车票价格:1.5走路到公交站时间:9
    车内时间:35
    地铁车票价格:5.0走路到地铁站时间:12
    车内时间:15
    下载: 导出CSV

    表  2  表征心理潜变量的显变量

    Table  2.   Manifest variables to indicate psychological latent variables

    潜变量显变量符号
    lc 车辆运行稳定很重要 c1
    车厢内的气味、温度、噪声很重要 c2
    出行途中可以看手机或书很重要 c3
    出行途中可以休息或放松很重要的 c4
    lr 会考虑出行方式的准点率 r1
    尽量避开时不时晚点的出行方式 r2
    即使多花 10 min 以上,尽量避开经常晚点的交通方式 r3
    尽量选择准点但不舒服的交通出行方式 r4
    lf 出行方式的便利性很重要 f1
    如果到达公交站的步行时间超过 10 min,我会选择其他交通方式 f2
    如果到达地铁站的步行时间超过 15 min,我会选择其他交通方式 f3
    如果候车时间太长,我会选择其他交通方式 f4
    下载: 导出CSV

    表  3  模型拟合度指标

    Table  3.   Fitness statistics of model

    类别RMSEACFITLISRMR
    模型值 0.076 0.950 0.931 0.041
    参考值[20] ≤ 0.080 ≥ 0.900 ≥ 0.900 < 0.080
    下载: 导出CSV

    表  4  验证性因子分析模型结果

    Table  4.   Results of confirmatory factor analysis

    潜变量显变量标准化系数ZP
    lcc10.75339.720
    c20.83050.550
    c30.39112.160
    c40.79344.160
    lrr10.84056.560
    r20.77645.430
    r30.79547.700
    r40.65929.390
    lff10.69618.770
    f20.52914.300
    f30.66922.910
    f40.94529.670
    下载: 导出CSV

    表  5  模型CAIC及BIC比较

    Table  5.   Comparison of CAIC and BIC values

    类别CAICBIC
    25 9055 882
    35 6205 568
    45 6275 579
    55 6575 580
    65 7095 614
    下载: 导出CSV

    表  6  潜在类别条件Logit模型回归系数

    Table  6.   Regression coefficient of latent-class conditional Logit model

    类别变量标准化系数ZP
    choice 1 f −0.107 −4.34 0
    w −0.130 −2.81 0.005
    v −0.076 −6.14 0
    dbus 0.212 0.29 0.772
    dmetro 3.075 3.77 0
    choice 2 f −0.121 −7.08 0
    w 0.100 2.48 0.013
    v −0.129 −5.10 0
    dbus −7.484 −4.55 0
    dmetro −3.672 −6.09 0
    choice 3 f −0.045 −3.67 0
    w −0.058 −3.19 0.001
    v −0.031 −4.09 0
    dbus 0.894 2.77 0.006
    dmetro 0.622 2.42 0.015
    下载: 导出CSV

    表  7  出行者特征对类别的影响

    Table  7.   Impact of travelers’ demographic characteristics on latent class

    类别变量标准化系数ZP
    choice 1 zfem 0.529 2.22 0.026
    zmar −0.370 −1.34 0.181
    zinc5 −0.332 −1.14 0.255
    zinc10 0.817 2.00 0.045
    zcar −0.360 −1.28 0.202
    zhou 0.212 0.76 0.446
    zc2work 0.669 1.70 0.089
    zb2work −0.590 −2.28 0.022
    zm2work 0.785 3.02 0.003
    lf 0.874 3.72 0
    lc 0.319 1.29 0.196
    lr 0.601 2.49 0.013
    zcons 0.076 0.26 0.797
    choice 2 zfem 0.375 1.49 0.135
    zmar −0.881 −2.97 0.003
    zinc5 0.267 0.88 0.378
    zinc10 1.022 2.52 0.012
    zcar 0.560 1.76 0.079
    zhou −0.371 −1.28 0.201
    zc2work 0.990 2.47 0.013
    zb2work −0.223 −0.80 0.422
    zm2work 0.053 0.19 0.850
    lf 1.000 3.94 0
    lc 0.008 0.04 0.971
    lr 0.101 0.44 0.662
    zcons −0.490 −1.50 0.132
    下载: 导出CSV

    表  8  相对系数对比

    Table  8.   Comparison of relative coefficient

    项目 $\dfrac{w}{f} \Bigg /\left( { {\simfont\text{元} }{\simfont\text{•} } {\rm{min} }^{-1} } \right)$ $\dfrac{v}{f} \Bigg /\left( { {\simfont\text{元} }{\simfont\text{•} } {\rm{min} }^{-1} } \right)$ dbus dmetro
    choice 1 1.2 0.7 −28.8
    choice 2 −0.8 1.1 62.0 30.4
    choice 3 1.3 0.7 −20.0 −13.9
    整体 0.6 0.8 14.3 −8.2
     注: choice 1 中的 dbus 的系数不显著,故未列出.
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-10-23
  • 录用日期:  2020-04-10
  • 修回日期:  2020-03-09
  • 网络出版日期:  2020-11-16
  • 刊出日期:  2021-02-01

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