Route choice in the presence of information using concepts from fuzzy control and approximate reasoning

The need for realistic route choice models has become essential in light of the ongoing 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. The authors present a modeling framework for route choice in the presence of information based on concepts from fuzzy set theory, approximate reasoning and fuzzy control. They use linguistic variables to model perceptions about 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 authors demonstrate the methodology through a small example and discuss calibration issues and implementation difficulties.