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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Pedestrian Exposure for Crash Prediction</title>
      <link>https://rip.trb.org/View/2259669</link>
      <description><![CDATA[This follow-on builds upon the framework established in a previous task order. Using data from Seattle/King County, Washington, the team developed and tested models of pedestrian exposure. The next step is to explore crash likelihood. At the intersection level, the relationship between pedestrian exposure measures (variables) and crash likelihood will be investigated. Analytical models will be developed that predict likelihood of pedestrian-vehicle crashes given pedestrian exposure measures. In addition, a sample of intersections will be used to examine associations between equity related factors (e.g., median household income, presence of sidewalks) and
crashes. This knowledge will help in future efforts in the development of tailored safety programs that encourage a Safe System approach wherein traffic safety professionals and other stakeholders can work together to implement multi-component countermeasure solutions to protect all road users.
]]></description>
      <pubDate>Mon, 02 Oct 2023 07:47:07 GMT</pubDate>
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