铁路疏解衔接系统用户细分是开展枢纽衔接优化的重要环节． 将潜在类别模型 与非集计混合 Logit 模型的似然函数进行融合，构建了一种能同时实现用户分类和行为分 析的潜类混合 Logit 用户细分模型;通过在潜在类别中设置衔接方式属性随机偏好参数， 实现了相同子市场用户间似而不同的属性偏好表达． 依托成都东客站到达旅客的衔接方 式选择 SP(陈述偏好)调查数据，借助 NLogit 软件编程对该模型的测试与标定过程进行了 说明，并结合标定结果对各衔接方式的市场总体时间弹性和费用弹性进行了计算，提出了 相应的管理措施． 结果显示，模型将铁路疏解衔接系统用户细分为“公交偏好型”、“私家 车偏好型”、“出租车偏好型”、“网约车偏好型”4 个子市场，不同子市场间呈现出差异化 的市场占有率、属性敏感性和属性偏好程度，验证了潜类混合 Logit 模型在市场细分中能 兼顾外源、内源性细分变量，并具有经济学解释能力强的特点．

Customer segmentation of railway egress shuttle system is one of the fundamental work for the optimiza- tion of intermodal connectivity for railway hubs． A latent class mixed Logit model for customer segmentation，which can realize the function of customer classification and behavior analysis at one time，was constructed by collabora- ting the likelihood function of latent class model with that of disaggregate mixed Logit model． With the settings of random preference parameters in the latent classes，it can accommodate the resembling but not homogeneous prefe- rences that customers have on attributes in the same sub-market． An example was given with the stated preference data collected towards the arrival passengers at Chengdu East Railway Station for their egress mode choices． NLogit software was used in the process of model testing and parameter estimation． Direct and cross elastics for time and cost of different egress modes were calculated and corresponding management policies were proposed to improve egress shuttle services． The results show that the market is segmented into 4 sub-markets that are “transit pre- ferred”，“private car preferred”，“taxi preferred”and“car-hailing preferred”，and each sub-market exhibits di- fferent market occupation rates，parameter significance levels，as well as attribute preferences． It proves the model ＇s feature of integrating both exogenous and endogenous variables in market segmentation as well as its powerful econometrical explanation ability in market analysis．