考虑潜在类别的市内机动化出行行为模型

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

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10000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.

To study the preference heterogeneity of travel choice and the influence of psychological factors on travel behavior,the psychological latent variables that influence the travel mode choice are obtained through confirmatory factor analysis.Then,these variables are introduced into latent-class conditional Logit model,which is solved by the expectation-maximization algorithm to obtain the number of latent classes and the utility function.Finally,Guangzhou is used as an example for empirical analysis.The results show that the latent-class conditional Logit model has higher fitness than the traditional conditional Logit model.For three travelers’groups:the metro-preference,car-preference,and bus-preference groups,which account for 42.5%,25.0%and 32.5%,respectively.The walking time value of the metro-preference and bus-preference groups is 1.2 Yuan/min and 1.3 Yuan/min,respectively,while t the car-preference group evaluate the walking positively.The time value of the metro-preference and bus-preference groups is 0.7 Yuan/min,which is less than that of the car-preference group of 1.1 Yuan/min.Whether the monthly income is more than 10000 Yuan and whether the travelers commute by car have a significant influence on the latent class classification.Of all psychological factors,flexibility and reliability have a significant influence on the latent class classification,while comfort have no significant influence.