Attitudinal attributes play an important role in behavior of individuals in various contexts. In this study we focus on the travel behavior and our main objective is to come up with segments of individuals that have different mode choice preferences with the help of the attitudinal attributes. These segments are important for the design of more efficient public transport policies specific to the characteristics of different customers. In order to identify the segments of individuals, most importantly the potential users of public transport, factor analysis techniques are utilized with the attitudinal attributes and the socio-economic characteristics of individuals. The learnings from this exploratory analysis are exploited in the construction of the class-membership model in our hybrid choice model. Maximum likelihood estimation is done simultaneously for the latent class model, including the measurement equations for the psychometric indicators, and the class-specific choice models. The results for the presented model with two latent classes show that middle-aged individuals with high income who are active in their professional and social life have higher value of time and are less elastic to the changes in the transport offer compared to the rest of the population.