Soft system modeling in transportation planning: Modeling trip flows based on the fuzzy inference system approach

Abstract

Transportation planning is one the most important problems of urban management systems. Meanwhile, modeling trip flows between metropolitan zones is vital to a successful transportation planning. Due to importance of the problem, different models have been developed in recent years but because of the complex nature of the problem that deals with human behavior and existence of different independent variables that affect number of trips, it is always hard to develop a model with acceptable forecasting error that is computationally efficient. In this paper a three phases fuzzy inference system (FIS) proposed to map social and demographic variables to total number of trips between origin-destination (OD), pairs. Fuzzy rule bases in the model are in fact the exploration of transportation experts’ subjective patterns.

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