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A two-stage framework for modeling discrete choice behavior in the presence of new information is presented. It is based on explicit information integration at the first stage, and a decision process based on the integrated information at the second stage. The first stage is conducted using an integration scheme which is source- and content-dependent, and the second stage is implemented using an approximate-reasoning-based choice model. The existence of an explicit information integration stage provides the advantage of improving the calibration procedure of the choice model by facilitating a two-phase calibration process in which both rules and membership functions are calibrated. A small case study demonstrates the applicability of the approach for modeling human route choice decisions in transportation networks when updated on-line traffic information is available to drivers. The case study also provides interesting insights on the tradeoffs between the number of rules and the importance of generating good membership functions, and explores the behavioral patterns of two types of drivers: familiar and unfamiliar. The suggested decision model is roughly compared to traditional random utility model, and provides favorable results.

The route choice problem in general, and in the presence of information in particular, is not a very well understood problem in the transportation literature. Most route choice models are based on the random-utility discrete-choice paradigm and assume that users choose the alternative with maximum utility value among the different alternatives. Recently, with the increased interest in the area of Intelligent Vehicle/Highway Systems and specifically Advanced Traveler Information Systems (ATIS), limitations of existing models have become very apparent. ATIS provide drivers with real-time traffic information in order to facilitate better route choice decisions. Under these conditions drivers are required to incorporate verbal, visual and prescriptive information into their own perceptions and consequently make route choices.