《Improving transportation impact analyses for subsidized affordable housing developments: A data collection and analysis of motorized vehicle and person trip generation》

打印
作者
Kristina M. Currans;Gabriella Abou-Zeid;Kelly J. Clifton;Amanda Howell;Robert Schneider
来源
CITIES,Vol.103,Issue1,Article 102774
语言
英文
关键字
Trip generation;Transportation impact analysis;Motorized vehicle trips;Person trips;Affordable subsidized housing;Parking supply
作者单位
College of Architecture, Planning, and Landscape Architecture, University of Arizona, 1040 N Olive Road, Tucson, AZ 85716, United States of America;Maseeh College of Engineering & Computer Science, Portland State University, 1930 SW 4th Ave #500, Portland, OR 97201, United States of America;Sustainable Cities Initiative, University of Oregon, Pacific Hall: 204, Eugene, OR 97403, United States of America;School of Architecture & Urban Planning, University of Wisconsin-Milwaukee, 2131 E Hartford Ave, Milwaukee, WI 53211, United States of America;College of Architecture, Planning, and Landscape Architecture, University of Arizona, 1040 N Olive Road, Tucson, AZ 85716, United States of America;Maseeh College of Engineering & Computer Science, Portland State University, 1930 SW 4th Ave #500, Portland, OR 97201, United States of America;Sustainable Cities Initiative, University of Oregon, Pacific Hall: 204, Eugene, OR 97403, United States of America;School of Architecture & Urban Planning, University of Wisconsin-Milwaukee, 2131 E Hartford Ave, Milwaukee, WI 53211, United States of America
摘要
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 sociodemographics.