Commute Travel Mode Choice Logit Model with Imprecision Explanatory Variable
Bing LI, Hiroyuki TAMURA
This paper develops a commute travel mode choice logit model with imprecision explanatory variables to forecast commute travel demand. In traditional travel mode choice logit models, all variables are used in utility function as precision variables. Others, in many fuzzy travel mode choice models, only imprecision variables are used. They will decrease the accuracy of models estimated. In this paper, we deal with imprecision variables using fuzzy reasoning method, then use them and precision variables in utility function of logit model. Excellent correspondence was achieved between the results obtained from using the model and the real data. We also predict the impact of the policy change.