Modeling the dynamic effect of information on drivers' choice behavior in the context of an Advanced Traveler Information System

In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users' changing perception of travel time also based on current network conditions. Drivers' choice models are often developed and calibrated by using Stated Preference (SP) surveys, amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experiment.