Neighborhood land use density variables and accessibility variables are shown to improve the
performance of trip-based travel demand models. As used in this research, density variables are based
on travel analysis zone land use data (e.g., households per residential acre, households per total
acre, retail employment per commercial/industrial acres); accessibility variables are based on
zone-to-zone travel times (e.g., number of retail jobs within "x" minutes transit or auto travel time).
Including these variables allows the analyst to predict changes in travel behavior due to increasing or
decreasing densities and accessibility to activities. Travel demand models are shown with and without
land use density and accessibility variables. Linear as well as nonlinear transformations of variables
are examined. This analysis discusses the importance of "disaggregate validation" of models to test for
statistical difference in travel models that include or exclude these variables. Research is based on
travel demand models developed by the metropolitan planning organization (MPO) for the nine-county San
Francisco Bay Area.
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