Abstract
This paper investigates the effect of day-to-day variability in individuals' travel behavior on the goodness-of-fit of travel demand models estimated with conventional cross-sectional data sets. In particular, this paper examines the effect of day-to-day variability on the goodness-of-fit of least squares regression models of person trip generation. The analytic results show that the conventional R-square goodness-of-fit measure for least squares regression models estimated with cross-sectional data is dependent upon two factors. The first factor is the proportion of the between-person variability that is accounted for by the explanatory variables in the model. The second factor is the proportion of the total variability in the dependent variable that is due to between-person variability. One week activity diary data are used to estimate the relative magnitude of the intrapersonal and interpersonal variability components for a variety of measures of trip-making. This analysis shows that intrapersonal variability may comprise a substantial proportion of the total variability, although the relative magnitude of the intrapersonal variability component varies with trip purpose and across population segments. Generally, however, intrapersonal variability is found to have a considerable effect on the apparent goodness-of-fit of person level trip generation models estimated with cross-sectional data. The paper also illustrates that recognizing the effect of intrapersonal variability on model goodness-of-fit may be useful in interpreting and evaluating model estimation and model transferability results.
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