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Understating Crash Risk Exposure of Low Income Neighborhoods and Households

It is well-known that socio-economic status (SES) is a predictor of crash risk, with lower-income, minority, and less-educated persons being disproportionately likely to be involved in a traffic crash and/or likely to be seriously injured in a traffic crash, most notably as pedestrians, but also as motorists and cyclists. This relationship, which is usually accounted for in safety research as a control measure rather than a direct relationship, is often attributed to explicit characteristics of lower-income crash victims themselves, such as their inability to afford a car (increasing the odds they will walk or cycle) or their inability to afford newer and more crashworthy vehicles. While these are certainly factors that may influence crash risk affecting lower-income households, it simplifies what is almost certainly a far more complex scenario. Lower-income households have fewer housing and transportation options, and are thus economically segregated into environments where lower-cost housing options are available. It is also likely that lower income neighborhoods are located closer to busier streets, industrial or commercial land uses, and farther away from major employment centers. Public services and street design in these neighborhoods may be obsolete or inadequate. These and other factors in the built environment may further contribute to the higher likelihood of crash risks in lower income neighborhoods. This study will examine the moderating role of the built environment on the relationship between crash incidence and SES. Orange County, FL, where the city of Orlando is located, will be selected as the study area. Compared to other states, Florida tends to have high traffic crashes, and in 2016 ranked number one in terms of Pedestrian Danger Index (PDI) calculated by Smart Growth America. The analysis will be done through a three-tiered process. The first is to examine the overall patterns of crash frequency and severity by stratifying neighborhoods by SES. The second step of the analysis is to map out the spatial patterns of TANF (Temporary Assistance for Needy Families) households and to examine whether crash incidence near TANF households exhibit unique crash patterns that differ from the overall crash pattern, and to compare them against environmental factors, such as population density, intersection configurations, and land use patterns. For the final tier, the findings from tiers 1 and 2 will be combined to understand the environmental factors that may place lower-income persons, particularly those participating in the TANF program, at disproportionate risk of traffic-related death and injury. The GIS database, including all the pertinent variables and spatial analyses, will be generated as an outcome of the project. The results and findings from the GIS and statistical analyses will in turn be used to make recommendations about both the types of design and policy interventions that may moderate crash risks for households receiving subsidies, as well as guidelines for the safe and appropriate siting and project design of housing for lower-income populations. The research results will be also disseminated to housing and community development agencies, and family and social services agencies in Orange County to help educate and advocate for transportation safety among lower income residents and neighborhoods.

Language

  • English

Project

  • Status: Active
  • Funding: $68,314
  • Contract Numbers:

    69A3551747113

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

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

    Collaborative Sciences Center for Road Safety

    University of North Carolina, Chapel Hill
    Chapel Hill, NC  United States  27514
  • Project Managers:

    Sandt, Laura

  • Performing Organizations:

    Florida Atlantic University, Boca Raton

    Boca Raton, FL  United States  33431
  • Principal Investigators:

    Li, Yanmei

    Dumbaugh, Eric

  • Start Date: 20180401
  • Expected Completion Date: 20190401
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01667896
  • Record Type: Research project
  • Source Agency: Collaborative Sciences Center for Road Safety
  • Contract Numbers: 69A3551747113
  • Files: UTC, RiP
  • Created Date: Apr 30 2018 10:23AM