Abstract: Based on the existing SP data of low-carbon commuting travel, the samples were clustered by using intuitionistic fuzzy c-means clustering algorithm to identify the subjective attitude types of residents toward low-carbon commuting travel. A MIMIC model of low-carbon commuting travel intention of different types of residents was constructed to study the differences of behavioral willingness formation mechanism among groups with different subjective attitudes. The research results show that the residents subjective attitudes toward low carbon commuting travels can be divided into three categories: positive, neutral and negative. There is a correlation relationship among residences subjective attitudes, travel mode choices and low-carbon commuting travel intention. The groups with different subjective attitudes influence the composition of the influencing factors of the behavior intention and there are differences in the path and intensity of influencing factors on behavioral intention.

Key words: traffic engineering, subjective attitudes identification, IFCM, MIMIC model, low-carbon travel

摘要： 基于已有的居民低碳通勤出行SP数据，应用直觉模糊C均值聚类算法对样本进行聚类，识别居民对低碳通勤出行所持有的主观态度类型。构建不同类型居民低碳通勤出行意愿的MIMIC模型，研究持有不同主观态度的群体其行为意愿形成机理的差异性。研究结果表明：居民低碳通勤出行的主观态度可划分为积极、中立、消极三类；主观态度与个体出行方式选择和低碳通勤出行意愿之间均存在相关性；持有不同主观态度的群体，作用于其行为意向的影响因素的构成，影响因素对行为意愿作用的路径，作用强度存在差异性。

关键词: 交通工程, 主观态度识别, 直觉模糊C均值聚类, MIMIC模型, 低碳出行