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dc.contributor.authorWang, Yinhai
dc.contributor.authorSun, Wei
dc.contributor.authorRicord, Sam
dc.contributor.authorde Souza, Cesar Maia
dc.contributor.authorYin, Shuyi
dc.contributor.authorTsai, Meng-Ju
dc.date.accessioned2021-10-21T22:58:24Z
dc.date.available2021-10-21T22:58:24Z
dc.date.issued2021-09-10
dc.identifier.urihttp://hdl.handle.net/11122/12306
dc.description.abstractThe 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.en_US
dc.language.isoen_USen_US
dc.subjectSafety Data Toolen_US
dc.subjectRoadway Safety Assessmenten_US
dc.subjectStatistical and Machine learning Modelingen_US
dc.subjectRuralen_US
dc.titleDeveloping a Data-Driven Safety Assessment Framework for RITI Communities in Washington Stateen_US
dc.typeTechnical Reporten_US
refterms.dateFOA2021-10-21T22:58:24Z


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