Information gain, novelty seeking and travel: a model of dynamic activity-travel behavior under conditions of uncertainty

When making a trip, individuals make observations that may increase their knowledge about their environment. In this paper, we develop a measure of expected information gain based on a Bayesian model of mental maps and belief updating. We argue that expected information gain is an element of the utility function of trip choice alternatives under conditions of limited information and learning. Theory and models are developed. The simulations conducted illustrate that expected information gain tends to favor longer trips and variety seeking in terms of both route and destination choice. We argue, therefore, that individuals may perceive a positive utility of travel through environments with which they are less familiar.