Abstract
Accurately modeling individual travel demand and behavior is essential for forecasting the impact ofalternative policies both at the disaggregated and aggregated levels. In the last decades, the state-ofthe-art of travel demand models advanced from traditional four-step models, passing through tourbasedmodels, to activity-based models. The latter models postulate that the demand for travel isderived from the demand for performing activities, i.e., travels are only undertaken when the utility ofan activity and its associated travel exceeds the utility of activities involving no travel [1]. Furthermore, itconsiders that daily travels are temporally and spatially constrained, and individuals start their day athome and return to a home base at the end of the day
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