A growing body of research shows that the traditional approaches employed to plan and forecast travel behaviors are not equipped to deal with the heterogeneity of behaviors over time, space, and social spheres. Therefore, travel policies struggle to reconcile social inclusivity, sustainability and network efficiency. Two ENAC laboratories propose to join forces – in mathematical modeling and quantitative sociology – to develop a novel multi-day activity-scheduling framework to forecast travel demand. Integrating day-to-day correlations in travel behaviors will lead to a better understanding of the motives behind travel decisions, and will unveil more facets of individual decision making for better predictions of their daily mobility choices. This research uses the MOBIS dataset, a 8-week / 3700-respondent travel survey conducted in Switzerland in 2019. The forecasting model will be applied to the Swiss synthetic population and several scenarios will be considered.