Capturing Latent Household Preferences in Daily-Activity Pattern Choices: Application to Activity-Based Model of Houston–Galveston Region in Texas

One fundamental feature of most operational activity-based models (ABMs) developed in the United States is the concept of a day activity pattern, which, in its broadest sense, is a way of characterizing all the activities undertaken in a day at the individual level. This pattern often includes a sequence of models that generate activities of different types for each individual. In many cases, these models treat all individuals in a household independently, while in other cases, specialized techniques capture intrahousehold relationships. This paper presents a new technique for capturing some of these intrahousehold relationships in a daily-activity pattern (DAP) model via terms for latent household preferences while also allowing for other specific relationships to emerge in more standard ways. The model is estimated on data from the Houston–Galveston region and serves as an extension to the DAP model framework being used in the ABM system under development for that region. The results suggest that strong household level preferences exist. For many activity pattern types, these household preferences are more important than the preferences of the individual. In addition, the modeling framework is concise, can easily accommodate households of any size, and can predict the exact number and type of mandatory tours (i.e., work, school, and university activities) for individuals in a single model.