Activity-based models: a comparison of approaches used to achieve integration among trips and tours throughout the day

Abstract

This study examines the so-called activity-based models implemented to date in the United States, explaining and comparing the various techniques that have been used to achieve model integration. These models integrate the representation of activities and travel conducted by an individual, and in some cases an entire household, over the course of an entire day. Such integration is what distinguishes these models from earlier trip-based and tour-based models. Three techniques of integration are typically used: Firstly, a model is developed that simultaneously represents outcomes spanning the tours in a day and, in some cases, the persons in a household. Sometimes called an model, it provides what could be called horizontal integration across all the dimensions of choice. Second, since the outcomes that need to be modeled are more complex than can be represented in a single activity pattern model, additional aspects of choice are modeled by breaking the outcome into a conditional model hierarchy or a chain of models. Models lower in the hierarchy (or later in the chain) take as given the outcomes higher in the hierarchy. This achieves what has been referred to as downward vertical integrity. Done properly, it assures that lower level models adhere to constraints imposed at higher levels, and makes the lower level models indirectly sensitive to all variables that directly affect the upper level outcomes. Just as important as downward integrity is upward vertical integrity. Upward integrity comes from making the upper level models appropriately sensitive to variables that affect the upper level outcome, but cannot be measured directly because they differ among the undetermined lower level model outcomes. In practice, a variety of techniques have been developed and used to achieve horizontal, downward and upward integrity. This paper examines and compares the techniques employed by five model systems that have been used for travel forecasting and policy analysis in the United States (in Portland, Oregon; San Francisco; New York City; Columbus, Ohio; and Sacramento). The techniques employed are not always directly comparable, the models are still relatively new, and the situations in which they are used vary considerably. Therefore, a meaningful empirical comparison of the techniques is not feasible. Accordingly, the emphasis in this paper is on providing a comparative conceptual understanding of the techniques themselves, including a reasoned discussion of the potential strengths and weaknesses of the various approaches. For the covering abstract see ITRD E145999

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