Inclusion of Latent Class in Behavior Model of Motorized Travel in City

To study the preference heterogeneity of travel choice and the influence of psychological factors on travel behavior, the psychological latent variables that influence the travel mode choice are obtained through confirmatory factor analysis. Then, these variables are introduced into latent-class conditional Logit model, which is solved by the expectation-maximization algorithm to obtain the number of latent classes and the utility function. Finally, Guangzhou is used as an example for empirical analysis. The results show that the latent-class conditional Logit model has higher fitness than the traditional conditional Logit model. For three travelers’ groups: the metro-preference, car-preference, and bus-preference groups, which account for 42.5%, 25.0% and 32.5%, respectively. The walking time value of the metro-preference and bus-preference groups is 1.2 Yuan/min and 1.3 Yuan/min, respectively, while t the car-preference group evaluate the walking positively. The time value of the metro-preference and bus-preference groups is 0.7 Yuan/min, which is less than that of the car-preference group of 1.1 Yuan/min. Whether the monthly income is more than 10000 Yuan and whether the travelers commute by car have a significant influence on the latent class classification. Of all psychological factors, flexibility and reliability have a significant influence on the latent class classification, while comfort have no significant influence.