Selecting mode choices on the basis of different behavior of passengers creates selection of different modes of transportation. Since the human being as an agent selector of mode choice has a different and random behavioral characteristics, the non-probability of mathematical models, can’t completely express the human behavior at mode choices of suburban trips. The aim of this study is to import whatever more behavioral characteristics on mode choices of suburban trips and more reliability the results of models with the use of fuzzy logic in them. In this regard for the mode choices of suburban trips a nested logit model was used. In order to consider the obscure behavior of the human in this model, variables of utility functions of each nest with using fuzzy subtractive clustering algorithm have been fuzzificated. Then calibration of the model with using the method of the maximum probability has been done. The results of this model with the data from the selected cities have been compared, clarifying the process modeling is satisfactory.
)
