United States Department of Transportation
i
Intelligent Safety Assessment of Rural Roadways Using Automated Image and Video Analysis [Research Brief]
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2023-12-01
[PDF-704.71 KB]
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Abstract:This project introduces an innovative solution employing computer vision and machine learning algorithms to automate the roadside safety evaluation process. Utilizing pre-trained models such as VGG16 and images captured from Utah roadways, the research team develops a robust algorithm for automated safety evaluation that aligns with the FHWA rating system, providing a comprehensive and efficient method for assessing roadside conditions. Tailored computer vision algorithms detect specific features, enhancing the accuracy of safety evaluations. Pre-trained models for clear zone detection and roadside slope classification further contribute to a nuanced understanding of roadside elements. The methodology employs various computer vision algorithms to automatically rank roadside safety by detecting features such as guardrails, clear zones, rigid obstacles, and roadside slopes.
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