Moving Beyond the Individual: Activity-Based Modeling of Time Use and Travel Behavior Incorporating Intra-Household Interactions

Abstract

The activity-based approach to the study of travel behavior implies a shift in focus from discrete trips to activities. A fundamental tenet of this approach is that individuals, when making their own activity-travel decisions, tend to interact with other members within a household. However, most activity-based research to date has been conducted at the individual level, but not at the household level. It is now well recognized that incorporating intra-household interactions is crucial to the development of improved activity-based models, which allow for more accurate travel demand forecasts and policy evaluations. In this context, the studies described in this dissertation have been conducted to explore several critical issues that have remained largely neglected in past studies. One such issue is the identification of joint participation in activity and travel episodes, due to the fact that most activity-travel surveys have failed to collect information on involved persons. In this dissertation, an integrated spatio-temporal GIS toolkit is initially developed to automatically identify and visualize (3D) joint activity/travel episodes. Such identification makes it possible to uniquely and directly incorporate intra-household interactions into studies of activity/travel behavior. The research described in this dissertation utilizes the 2003 CHASE (Computerized Household Activity Scheduling Elicitor) survey collected in the Greater Toronto Area. Several aspects of activity/travel behavior are investigated.. First, quantitative models are developed and estimated for investigating household activity time use patterns while capturing intra-household interactions. Second, the dynamics of household time use patterns are explored through descriptive analysis and structural equations models. Finally, the household activity decision-making process is further delved into with a focus on the planning priority of joint activities. Overall, the research presented in this dissertation makes important contributions to activity-based time use and travel behavior research: (1) technically, the developed GIS toolkit is helpful to reduce costs of processing large activity-travel datasets; and (2) theoretically, the empirical results presented will form the basis toward the development and implementation of an improved activity-based model.