现有的出行方式选择行为模型仅考虑了可直接观测的出行者的个人社会经济特性和出行方案特性,并未考虑影响选择结果的潜变量,为此,文中提出了出行行为中潜变量的概念,并通过结构方程模型( SEM) 刻画潜变量与显变量、潜变量与其测量变量之间的因果关系. 然后,基于最大效用理论,对Logit 模型的出行方式效用函数进行改进,构建了潜变量与显变量共同作用的SEM-Logit 整合模型. 结果表明:考虑了潜变量的整合模型的优度比传统Logit 模型提高了0. 201,最大似然函数估计值增加了20. 607,证明潜变量对出行方式选择行为存在显著影响,所提出的整合模型的解释能力和精度较高.

In the existing model of travel mode choice behaviors, only the observable characteristics of the traveler's socioeconomic status and travel plan are considered, while the latent variable (LV) affecting the travel mode choice is ignored. In order to solve this problem, the concept of LV in travel behaviors is proposed, and the causal rela-tionships between the LV and the manifest variable as well as between the LV and its measurement variables are de-scribed by using a structural equation model (SEM). Then, based on the maximum utility theory, a SEM-Logit in-tegration model containing both the LV and the manifest variable is constructed by improving the utility function of travel mode in the Logit model. The results show that, as compared with the traditional Logit model, SEM-Logit in-tegration model improves the goodness and the maximum likelihood value respectively by 0. 201 and 20. 607, which means that the LV plays an important role in travel mode choice behaviors and that the proposed model is of higher explanatory ability and accuracy.