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MPC |
| Title: | Intelligent Safety Assessment of Rural Roadways Using Automated Image and Video Analysis |
| Principal Investigators: | Nikola Markovic and Abbas Rashidi |
| University: | University of Utah |
| Status: | Active |
| Year: | 2021 |
| Grant #: | 69A3551747108 (FAST Act) |
| Project #: | MPC-669 |
| RiP #: | 01785292 |
| RH Display ID: | 159607 |
| Keywords: | automation, computer vision, highway safety, image analysis, machine learning, roadside, rural highways, video |
Due to the significant effect of roadside safety on the number and severity of road accidents, many state DOTs are trying to detect road segments with potentially unsafe roadside attributes. This can be achieved by manually inspecting videos and images collected by third-party data providers, such as Mandli. However, this process is both time-consuming and susceptible to human error. Therefore, this project will develop an automated approach that leverages computer vision and machine learning to efficiently evaluate roadside safety.
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