Fuzzy Trip Distribution Models for Discretionary Trips

Abstract

Trip distribution is considered as the second step in urban transportation planning. The important factors which affect trip distribution are the characteristics of origins and destinations and travel impedance between O/D. Trip distribution traditionally models with the deterministic variables although it seems affective variables in trip distribution molding are based on human perceptions. Since perceptions of people vary from one person to another, thus variables are imprecise and vague. Fuzzy approaches are proper tools of modeling non-deterministic variables. In this paper we present fuzzy estimation models of trip distribution for discretionary trip purposes including: shopping, personal, and recreation trips. Trip distribution estimation models apply fuzzy rule base which is generated by application of two procedures including Wang and Mendel, and Wang. Fuzzy rule base will be enhanced by expert knowledge; therefore the fuzzy prediction model will be more accurate. In this article fuzzy rule base generated by Wang procedure is improved by expert knowledge. Real data obtained from comprehensive transportation study of Shiraz, a large city in Iran, is used to develop conventional gravity and fuzzy models. The results of case study show that fuzzy model can be improved in order to accurately predict trip distribution regard to gravity model.