Abstract
This study introduces a model of individual belief updating of subjective travel times as a function of the provision of different types of travel information. Travel information includes real-time prescriptive or descriptive, and public or personal information. The model is embedded in a start-of-the art multi-state supernetwork representation of individual daily activity-travel scheduling behavior. The belief updating process of subjective travel times under information provision is based on Bayes’ Theorem. The multi-state supernetwork predicts daily activity travel choices based on the minimization of generalized costs related to the full activity-travel pattern. These generalized costs are based on expected travel times across the network. Thus, the simulation model will capture changes in activity-travel scheduling decisions that are made by individuals after updated their beliefs about expected travel times when receiving new travel information.
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