Forecasting Bicycle Facility Demand to Estimate Societal Impacts (Phase II)

In 1994 President Clinton issued Executive Order (EO) 12898 which directs Federal Agencies to identify and avoid negative impacts: “Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations”. The EO directs each Federal Agency to “make achieving environmental justice part of its mission by identifying and addressing, as appropriate, disproportionately high and adverse human health or environmental effects of its programs, policies, and activities on minority populations and low-income populations,” including tribal populations. Although the EO is clearly aimed to identify and reduce negative impacts, provision of bicycle facilities to environmental justice (EJ) as well as other population segments may have significant, identifiable positive impacts but very little has been done to document positive bicycle facility impacts. A first step toward identifying positive impacts is estimation of usage by EJ as well as the population in general. There has been some work performed to estimate impacts of bicycle facilities but very little has directly examined impacts on EJ or other specific population segments and available tools for forecasting numbers of bicycle users, much less, estimating impacts are relatively scarce. Most methods for estimating impacts of bicycle facilities have been focused on very large-scale analyses, however, impacts of specific bicycle facilities or impacts upon specific population segments are rarely reported. Potential positive impacts of bicycle facilities are dependent upon the numbers of bicycle riders who actually use the facility once it is constructed. Predictive models for bicycle facility usage are developed using a combination of bicycle facility user counts, origin-destination surveys and socioeconomic data. A direct estimation method as well as a two-step estimation procedure are developed to estimate usage of a proposed bicycle facility. The use of zonal socioeconomic characteristics as predictor variables is intended to enable the models to predict bicycle facility usage by population segments. Usage predictions can form the basis for broad spectrum estimates of bicycle facility impacts upon health, food availability, employment access and ultimately regional sustainability.

    Language

    • English

    Project

    • Status: Active
    • Funding: $112500
    • Contract Numbers:

      69A3551747133

    • Sponsor Organizations:

      Center for Advanced Multimodal Mobility Solutions and Education

      University of North Carolina, Charlotte
      Charlotte, NC  United States  28223

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      University of North Carolina, Charlotte

      Department of Civil and Environmental Engineering
      9201 University City Boulevard
      Charlotte, NC  United States  28223-0001
    • Project Managers:

      Fan, Wei

    • Performing Organizations:

      University of Texas at Austin

      Austin, TX  United States  78712
    • Principal Investigators:

      Machemehl, Randy

    • Start Date: 20181001
    • Expected Completion Date: 20200930
    • Actual Completion Date: 0

    Subject/Index Terms

    Filing Info

    • Accession Number: 01699745
    • Record Type: Research project
    • Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
    • Contract Numbers: 69A3551747133
    • Files: UTC, RiP
    • Created Date: Mar 24 2019 4:09PM