出行者到达枢纽站的交通方式效用是交通出行选择的重要因素;另一方面，出行 者方式的偏好具有显著的异质性，传统的离散选择模型不能很好地解释出行者异质性． 本 研究利用潜在类别条件 Logit 模型研究高铁站出行者的出行选择行为． 潜在类别条件 Logit 模型考虑出行者异质性，在对出行者进行潜在类别划分的同时得到不同类别的出行者的出 行行为效用函数． 研究结果表明，将出行者划分为3 个类别． 不同类别出行者在步行时间、车 内时间、价格、公交偏好、地铁偏好等方面具有显著差异． 此外，出行者小汽车拥有情况、月收 入等个人属性以及灵活性、舒适性、可靠性等潜在心理变量会影响出行者的类别划分．

Utilities of travelers' arrival modes to a hub station are important factors that affect travelers' mode choice． There is heterogeneity among travelers' preference of mode choice，and the traditional discrete choice mode can't explain the heterogeneity clearly． This study incorporated the heterogeneity into travelers' mode choice to the high-speed railway station with the latent class conditional Logit model． The latent class conditional Logit model produced segment-specific parameter estimates to capture heterogeneous preferences for choice alternatives and identified travelers' profiles for each segment． The results show that the sample population can be divided into three subgroups，and the parameters of in-vehicle time，walking time and price varies in each subgroup． Further- more，the car-ownership，monthly income and latent variables (flexibility，comfort，reliability) have significant influences on the category classification of the sample population．