Optimize the Work Zone Safety with Spatial Information Technology and Eye Tracker

Construction in the United States has consistently experienced higher fatality and injury/illness rates. While many studies have highlighted the importance of attention in reducing the number of injuries in the construction industry, few have attempted to measure the actual effectiveness of vibrant markers on hazard identification. The objective of the proposed research aims to integrate remote sensing with Eye Tracker to analyze and quantify the effectiveness of construction safety signs. This research will also propose a new mechanism to optimize the layout of the construction safety sign based on the global positioning system (GPS) and point cloud data. Phase one of the study will be conducted in the laboratory condition to determine how well the warning labels improve the speed and accuracy in which construction workers are able to locate and identify hazards. Phase two will be conducted in the real construction environment. Eye-tracking will be performed and be integrated with remote sensing to perform a safety simulation and to optimize the layout of the construction safety sign. This research increases the construction field's understanding of the variables that impact attentional allocation and provide a novel approach for improving construction site safety by using Eye-tracking technologies and remote sensing.


  • English


  • Status: Completed
  • Funding: $93359
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Mountain-Plains Consortium

    North Dakota State University
    Fargo, ND  United States  58108
  • Project Managers:

    Tolliver, Denver

  • Performing Organizations:

    Dept. of Civil and Architectural Engineering

    University of Wyoming
    Laramie, WY  United States 
  • Principal Investigators:

    Zhang, Chengyi

  • Start Date: 20210507
  • Expected Completion Date: 20220731
  • Actual Completion Date: 20220909
  • USDOT Program: University Transportation Centers Program
  • Source Data: MPC-653

Subject/Index Terms

Filing Info

  • Accession Number: 01773374
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: 69A3551747108
  • Files: UTC, RIP
  • Created Date: May 27 2021 4:30PM