Abstract
The idea of livable communities suggests that people should have the option to utilize non-motorized travel (NMT), specifically walking and bicycling, to conduct their daily tasks. Forecasting personal travel by walk and bike is necessary as part of regional transportation planning, and requires fine detail not only about individual travel, but also on transportation and neighborhood infrastructure. In an attempt to characterize the 'market' potential for NMT, the Office of Planning, Federal Highway Administration (FHWA) funded the Center for Transportation Analysis (CTA) of the Oak Ridge National Laboratory (ORNL) to conduct a study. The objectives of this effort were to identify factors that influence communities to walk and bike and to examine why, or why not, travelers walk and bike in their communities. This study relied on information collected under the 2009 National Household Travel Survey (NHTS) as the major source of data, and was supplemented with data from the American Community Survey (ACS), educational survey, health, employment, and others. Initial statistical screening methods were applied to sort through over 400 potential predictor variables, and examined with various measures (e.g., walk trip per person, walk mileage per person, bike trip per person, bike mileage per person) as the dependent variables. more » The best geographic level of detail used in the modeling for this study was determined to be the Census block group level for walking and Census tract level for biking. The need for additional supplemental private data (i.e., Walk Scores and Nielsen employment data), and geospatial information that reflects land use and physical environments, became evident after an examination of findings from the initial screening models. To be feasible, in terms of costs and time, the geographic scale of the study region was scaled down to nine selected NHTS add-on regions. These regions were chosen based on various criteria including transit availability, population size, and a mix of geographic locations across the nation. Given the similarities in modeling results from walk trips and walk mileages, additional modeling efforts conducted under the later part of this study were focused on walk trips per person. Bike models were limited only with the stepwise logistic models using Census tracts in the selected regions. Due to NHTS sampling limitations, only about 12% of these tracts have bike trips recorded from NHTS sampled households. The modeling with NHTS bike data proved to be more challenging and time consuming than what was anticipated. Along with the late arrival of Nielsen employment data, the project team had to limit the modeling effort to focus on walking. Therefore, the final modeling and discriminant analysis was conducted only for walking trips. « le
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Published on 01/01/2012
Volume 2012, 2012
DOI: 10.2172/1045233
Licence: CC BY-NC-SA license
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