Improving Transportation Impact Analyses for Subsidized Affordable housing developments: A data collection and analysis of motorized vehicle and person trip generation

Transportation impact analyses begin with a trip generation estimation process—estimating motorized vehicle and person trip counts coming and going from the proposed site. Data commonly used is often insensitive to urban contexts (such as employment densities) and socioeconomic conditions. This insensitivity results in sometimes exaggerated estimates, an increase associated transportation impact fees, and a need for additional mitigation of impacts which may further hinder land development. In this study, we collected and analyzed person and motorized vehicle count data from 26 affordable housing developments in Los Angeles and San Francisco. Counts were regressed upon site and built environment characteristics known to influence site-level travel behavior (e.g., parking supply, employment density), and regressions were validated using externally collected data. The findings indicate the average square footage of dwelling units, parking ratios, and nearby retail employment densities to be important predictors. The findings also indicate that increasing the parking supply from one space to two for each dwelling unit will result in a significant predicted increase of approximately 0.26 and 0.18 motorized vehicle trips per dwelling unit for AM and PM peak periods, respectively. These findings reiterate the need for trip generation methodologies sensitive to the built environment and sociodemographic