Models for route choice behavior in the presence of information using concepts from fuzzy set theory and approximate reasoning

The need for realistic route choice models has become essential in light of the on going research in the IVHS (Intelligent Vehicle Highway Systems) area, where drivers are required to incorporate verbal, visual and prescriptive information into their own perceptions while making route choices. We present a modeling framework for route choice in the presence of information based on concepts from fuzzy set theory, approximate reasoning and fuzzy control. We use fuzzy sets to model perceptions of network attributes, and traffic information provided by an information system. Rules of the form: “if ... then ...” are used to model the decision process, and to describe attitudes towards taking a specific route given (possibly vague) perceptions on network attributes. The rules are used as anchoring schemes for decisions, while the adjustment of the rules to changing conditions is done by an approximate reasoning mechanism. The suggested approach provides a route choice model in which the final choice is a combination of various considerations each of which captures a certain aspect of the final decision in a non-linear fashion. We demonstrate the methodology through a small example and discuss calibration issues and implementation difficulties.