Abstract
This paper provides extensions to the Household Activity Pattern Problem (HAPP) to help move existing formulations from a laboratory prototype toward a more usable activity-based demand modeling product. Previous research on HAPP has been based on a pickup and delivery problem with time window constraints (PDPTW), which does not lend itself easily to application compatible with an activity-based forecasting model. Meanwhile, other research on activity based modeling lacks of the integration of household decisions on time of day arrival, activity duration and traffic congestion effect on travel. For the demand side, the authors propose to incorporate time-of-day factors influencing both activity arrival and activity duration utility into HAPP as decision variables. Alternatively, for the supply side, the authors extend HAPP to capture the time-of-day (TOD) differences in travel times and costs to form the travel time-dependent utility household activity pattern problem model (TUHAPP). In their synthetic examples, the authors demonstrate how TUHAPP handles impacts of policy changes on peopleâ??s departure and activity duration decisions and how traffic congestion can change peopleâ??s travel agendas.