MPC
Project Details

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:	Completed
Year:	2021
Grant #:	69A3551747108 (FAST Act)
Project #:	MPC-669
RH Display ID:	159607
Keywords:	automation, computer vision, highway safety, image analysis, machine learning, roadside, rural highways, video

Abstract

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.

Project Deliverables

• [Final Report] Intelligent Safety Assessment of Rural Roadways Using Automated Image and Video Analysis — MPC-23-510
  • View Research Brief

Project Word Files

• Show project Word files
  • Full Description (Word, 2277K)
  • UTC Project Information (Word, 23K)

  Note to project PIs: please use the Track Changes feature when editing the above Word file(s). Updated document(s) should be emailed to ndsu.ugpti@ndsu.edu.