Assessing the Value of LiDAR in Detecting Conflicts at Intersections to Enhance Safety

The goal of this research is to evaluate and compare the effectiveness of camera-based and LiDAR-based systems for detecting traffic conflicts. AI-based methods will be developed and applied separately to datasets collected from each sensing platform. The study will assess the performance of each system in terms of conflict detection accuracy at three sites representing varied environmental and traffic conditions. In addition to technical performance, a cost-benefit assessment will be conducted to evaluate the practicality and scalability of each sensing approach.

Language

• English

Project

• Status: Active
• Funding: $200,000.00
• Contract Numbers:

  GDOT RP 25-15

• Sponsor Organizations:

  Georgia Department of Transportation

  One Georgia Center
  600 West Peachtree Street, NW
  Atlanta, GA  United States  30308
• Managing Organizations:

  Georgia Department of Transportation

  One Georgia Center
  600 West Peachtree Street, NW
  Atlanta, GA  United States  30308
• Project Managers:

  Jordan, Kamari

• Performing Organizations:

  University of Georgia Research Foundation (UGARF)

  310 E. Campus Rd.,
  Athens, GA  United States  30602
• Principal Investigators:

  Li, Qianwen

• Start Date: 20250730
• Expected Completion Date: 20270730
• Actual Completion Date: 0
• USDOT Program: Advanced Research
• USDOT Program: System Capacity, Planning and Improvements
• Subprogram: AI Communication Platform for Revenue Expansion
• Subprogram: Enhancing Technology Resources for Increased Mobility Options

Subject/Index Terms

• TRT Terms: Artificial intelligence; Benefit cost analysis; Cameras; Data analysis; Datasets; Laser radar; Traffic conflicts; Traffic surveillance
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01965067
• Record Type: Research project
• Source Agency: Georgia Department of Transportation
• Contract Numbers: GDOT RP 25-15
• Files: RIP, STATEDOT
• Created Date: Sep 9 2025 8:19AM