考虑个体异质性的汽车分时租赁选择行为

传统交通行为模型缺乏对个体异质性的考虑，导致其对真实选择行为的解释可能存在差距. 为了研究个体异质性对出行选择行为的影响，首先，分别构建了基于混合logit的选择模型以及基于潜在类别条件logit的选择模型；其次，使用正交设计法生成意愿调查问卷，在成都市开展新能源汽车分时租赁的出行选择实证调查；最后，利用极大似然模拟，采用Halton序列抽样对混合logit模型进行标定；采用回归分析对潜在类别条件logit模型进行求解. 结果表明:步行时间、候车时间、车内时间以及出行费用是影响出行方式选择的关键因素，两种模型均反映出个体异质性对出行者选择行为有着显著影响；潜在类别条件logit模型的拟合优度为0.143，优于混合logit模型的0.139，前者命中率为77.85%，也高于后者的61.28%；潜在类别条件logit模型将出行者划分为3个类别，区分度为0.908 4；类别1群体对出行费用最为敏感，对候车时间不敏感；类别2群体对步行时间和候车时间更加敏感，对费用敏感程度较低；类别3群体对时间和费用的敏感程度介于类别1和类别2之间. 

Choice Behavior of Time-Sharing Vehicle Leasing Considering Individual Heterogeneity

Lack of individual heterogeneity in traditional travel behavior models causes errors in the interpretation of real choice behaviors. In order to explore the influence of individual heterogeneity on travel choice behavior, firstly, a mixed logit based choice model and a latent-class conditional logit based choice model are built. Secondly, orthogonal design method is used to generate stated preference questionnaires for an empirical survey in Chengdu regarding travel choice behaviors of time-sharing lease on new energy vehicles. Finally, the mixed logit model is calibrated by using maximum likelihood simulation and Halton sequence sampling. The latent-class condition logit model is solved by regression analysis. The results show that access time, waiting time, in-vehicle time and cost are the key factors in choosing urban traffic modes. Both two models reveal that individual heterogeneity has a significant influence on travelers’ choice behaviors. The latent-class conditional logit model has a higher goodness of fit of 0.143 and a hit ratio of 77.85%, compared to those of 0.139 and 61.28% for the mixed logit model. Besides, the latent-class conditional logit model divides travelers into three categories, and the degree of differentiation is 0.908 4. Group 1 is most sensitive to cost but insensitive to waiting time; group 2 is more sensitive to access time and waiting time than cost; group 3 has an intermediate sensitivity to time and cost.