Modeling household interactions in daily activity generation

This dissertation seeks to contribute to the area of activity-based travel- demand modeling by examining the impacts of inter-personal interactions within a household on the daily activity participation choices of individuals. A comprehensive analysis framework is developed for modeling the weekday, in-home and out-of- home activity participation choices of adults in active, nuclear-family households, as an outcome of individual and household needs, desires, opportunities, and spatio- temporal and resource constraints. The analysis framework explicitly captures several kinds of interactions between the household heads, such as sharing of household-maintenance tasks, engagement in joint activities, and the trade-offs between independent and joint discretionary activity participation. In addition to these inter-personal interactions, the intra-personal trade-offs among the different activity participation choices are also accommodated in this framework. The empirical model system in this study comprise the following three components: (1) a seemingly unrelated regressions model for in-home maintenance activity generation, (2) a joint mixed-logit hazard-duration model for out-of-home maintenance activity generation, and (3) a multiple discrete-continuous (binary logit - linear regression) model system for discretionary activity generation. These models are estimated using data from the 2000 Bay Area Travel Survey. This research also develops a micro-simulation framework for using the model system for predicting disaggregate, household-level, activity-participation choices. Thus, the modeling framework developed in this dissertation, can be embedded as an enhanced “activity-generation module” within a comprehensive micro-simulation-based activity-travel forecasting system. Finally, an application of the developed micro-simulation framework for the analysis of the impacts of policy actions on the inter-dependent daily activity participation choices of adults is presented. In the overall, this research is envisioned as a very important first step in the development of an operational, activity-based, travel-demand forecasting system that comprehensively accommodates various intra-personal and inter-personal linkages in daily activity-travel choices.