Observed travel patterns are the result of an underlying activity-scheduling process. Understanding how individuals plan and sequence their activities and trips over time will offer promise, as researchers are interested in developing models that can predict the sequences in which activities are added to the schedule during a continuous process of schedule construction. In practice, a fixed order by activity type is often assumed, but it ignores the strong interdependencies in activity and travel choices. This study presents the process of developing a mixed logit discrete choice model to predict the choice of the activity-scheduling time horizon. The model classifies activities according to the order in which they were planned (weeks or months ago, same week, same day, or impulsive). A variety of explanatory variables were used to provide a good model fit. Overall, the model demonstrates that activity planning is influenced by a wide variety of explanatory variables, including observable activity types and characteristics, spatial-temporal flexibility, and household and individual characteristics.
Abstract