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dc.contributor.authorWang, Yinhai
dc.contributor.authorSun, Wei
dc.contributor.authorRicord, Sam
dc.contributor.authorMaia de Souza, Cesar
dc.contributor.authorLing, Yifan
dc.contributor.authorShi, Yan
dc.contributor.authorWang, Bingzhang
dc.contributor.authorNasri, Mehrdad
dc.date.accessioned2024-07-29T20:29:20Z
dc.date.available2024-07-29T20:29:20Z
dc.date.issued2024-07
dc.identifier.urihttp://hdl.handle.net/11122/15263
dc.description.abstractThis report presents the Mobile Unit for Sensing Traffic (MUST) project, which addresses the critical need for comprehensive traffic data in tribal and rural areas that often suffer from disproportionately high rates of traffic incidents due to limited infrastructure and resources. By implementing a low-cost, user-friendly data collection system, the MUST project aimed to provide real-time traffic information to significantly enhance traffic safety. The pilot installation in Yakama Nation, Washington, at a high-traffic intersection known for frequent accidents, marks a crucial step in this initiative. Collaboration with the Yakama Nation's Tribal Traffic Safety Coordinator and Yakama Power ensured the successful installation and operation of the sensor on a strategically selected telephone pole. Equipped with advanced machine learning technology, the MUST system collects detailed data on traffic flow, road surface conditions, and environmental factors such as temperature and humidity, visualized through a sophisticated dashboard for real-time monitoring and data-driven decision-making. This system allows for the identification of high-risk areas and the implementation of targeted safety measures, such as improved signage and road maintenance, while addressing specific concerns like pedestrian safety, visibility issues due to heavy fog, and speeding. By providing a robust dataset previously unavailable, the MUST project supports the Yakama Nation’s efforts to understand and mitigate traffic safety issues, ultimately enhancing the overall safety and quality of life for the community. This pilot project serves as a model for other tribal and rural areas looking to leverage advanced technology to improve their transportation safety infrastructure.en_US
dc.language.isoen_USen_US
dc.subjectSafety Data Toolen_US
dc.subjectRoadway Safety Assessmenten_US
dc.subjectPedestrian safetyen_US
dc.subjectcollisionsen_US
dc.subjectseverityen_US
dc.subjectHSS databaseen_US
dc.subjectMachine learningen_US
dc.subjectstatistical modelingen_US
dc.subjectclassification methodsen_US
dc.titleCost-Effective System for Rural Roadway Traffic, Surface Conditions and Weather Conditions Monitoringen_US
dc.typeTechnical Reporten_US
refterms.dateFOA2024-07-29T20:29:22Z


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