Multi-day activity scheduling reactions to planned activities and future events in a dynamic agent-based model of activity-travel behavior

Modeling multi-day planning has received scarce attention today in activity-based transport demand modeling. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities and parameter values. The results show that the model works well and that the influences of the parameters are consistent, logical and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach