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    Developing a Data-Driven Safety Assessment Framework for RITI Communities in Washington State

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    1905_CSET_Final Report.pdf
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    Author
    Wang, Yinhai
    Sun, Wei
    Ricord, Sam
    de Souza, Cesar Maia
    Yin, Shuyi
    Tsai, Meng-Ju
    Keyword
    Safety Data Tool
    Roadway Safety Assessment
    Statistical and Machine learning Modeling
    Rural
    Metadata
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    URI
    http://hdl.handle.net/11122/12306
    Abstract
    The roadway safety of the Rural, Isolated, Tribal, or Indigenous (RITI) communities has become an important social issue in the United States. Official data from the Federal Highway Administration (FHWA) shows that, in 2012, 54 percent of all fatalities occurred on rural roads while only 19 percent of the US population lived in rural communities. Under the serious circumstances, this research aims to help the RITI communities to improve their roadway safety through the development of a roadway safety management system. Generally, a roadway safety management system includes two critical components, the baseline data platform and safety assessment framework. In our Year 1 and Year 2 CSET projects, a baseline data platform was developed by integrating the safety related data collected from the RITI communities in Washington State. This platform is capable of visualizing the accident records on the map. The Year 3 project further developed the safety data platform by developing crash data analysis and visualization functions. In addition, various roadway safety assessment methods had been developed to provide safety performance estimation, including historical accident data averages, predictions based on statistical and machine learning (ML) models, etc. Beside roadway safety assessment methods, this project investigated the safety countermeasures selection and recommendation methods for RITI communities. Specifically, the research team has reached out to RITI communities and established a formal research partnership with the Yakama Nation. The research team has conducted research on safety countermeasures analysis and recommendation for RITI communities.
    Date
    2021-09-10
    Type
    Technical Report
    Collections
    CSET Project Reports

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