本项目探索互联网+背景下‘小汽车/停车换乘地铁’精细化多模式出行信息(例如交通方式服务水平属性的详细信息)对出行者交通方式选择的影响机理。首先，以混合选择模型(HCM)为理论基础，构建考虑‘个性特征、态度、价值’三类个体心理特征和‘社会网络影响’的交通方式选择模型；采用层次结构的潜变量子模型刻画心理特征的复杂影响，运用Mixed Logit构造用于解决‘解释变量重要性不均一性’、‘重复观测结果相关性’和社会网络影响等建模难点的离散选择子模型，细致刻画信息影响机制。其次，提出多模式出行信息下交通方式选择行为的数据调查方法并获取数据。然后，通过交通方式选择模型实证研究得到多模式信息、交通方式属性、个体属性、心理特征、社会网络等各类影响因素与交通方式选择概率之间的定量关系，揭示多模式信息的影响机理。最后，通过模型应用给出交通对策建议。成果可为需求建模、信息系统设计和政策制定提供理论和实践依据。

This study, in the context of Internet +, investigates the impact of ‘Auto/Subway Park-and-Ride’ fine-grained multi-modal traveler information (e.g. detailed level-of-service attributes information) on travelers’ travel mode choice. Firstly, taking the hybrid choice model as theoretical frame of research, it develops a mode choice model which both consider ‘individual mental characteristics’, ‘attitudes’, and ‘values’, and consider a traveler’s social network influence. It uses the latent variable sub-model with hierarchical structure to capture complex influence of psychometric factors. It develops a mixed logit based discrete choice sub-model to address ‘heterogeneity in value of explanatory variables’, ‘correlations among repeated observations’, and social network influence. Secondly, it proposes a data collection method for mode choice behavior under multi-modal traveler information and obtains the behavioral data. Thirdly, it conducts an empirical study of the developed mode choice model to obtain the quantitative relationship among multi-modal traveler information, travel mode attributes, socio-demographic attributes, psychological characteristics, social network influence, and mode choice probability, which reveals the mechanism for the impact of multi-modal traveler information. Last, model applications and associated suggestions are given. Research results can provide both a methodological basis and practical guidance for such tasks as travel demand modeling, travel information system design, and policymaking.