Abstract
Travel demand models are valuable tools in the transportation planning process; based on sound theory, these models bring a quantitative element to what is predominantly a political process. The forecasts output from these models guide decision makers in evaluating and selecting transportation programs and projects. Developing a better understanding of the factors that influence travel behavior, the changes in travel behavior over time, and the variables that best capture these changes may lead to the development of models that are more stable over time, increase the analyst's confidence in model results and lead to more cost-effective investment decisions. This paper investigates the life cycle as one such class of variables. In this context, “life cycle” is defined as the stage a family is in at a given time as related to factors such as the number and age of adults in the household; the presence, number, and age of children; and worker status. Using various statistical tests to evaluate the usefulness of the life cycle, the paper presents evidence to indicate that the life cycle has a strong influence on trip-making behavior while also improving stability in trip rates over time. These findings suggest that advanced trip generation models that accommodate more independent variables may lead to improved models, are more temporally stable, and better capture the dynamics that influence trip making.
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