Studying the Use of Low-Cost Sensing Devices to Report Roadway Pavement Conditions

This report investigates the application of low-cost sensing technologies, including Global Positioning Systems (GPS), accelerometers, and smartphones, to monitor roadway pavement conditions in real time. By leveraging widely available sensors embedded in vehicles, this research demonstrates how machine learning models can detect and classify road anomalies, such as cracks and potholes, significantly improving road safety and reducing operational costs. The study also presents a mixed integer linear programming (MILP) model to optimize maintenance and repair (M&R) activities under budget constraints. These models help transportation agencies prioritize road repairs, ensure efficient resource allocation, and minimize traffic disruptions. By adopting low-cost sensor-based approaches, municipalities can move toward more proactive, data-driven maintenance strategies, ultimately improving road network longevity and user satisfaction.

• Record URL:
  • https://www.ugpti.org/resources/reports/details.php?id=1228
• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/78991
• Summary URL:
  • https://rosap.ntl.bts.gov/view/dot/78992
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Colorado, Denver

  Department of Civil Engineering
  1201 5th Street, Room AD240C, P.O. Box 173364
  Denver, CO  United States  80217-3364

  Mountain-Plains Consortium

  North Dakota State University
  Fargo, ND  United States  58108

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Abdallah, Moatassem
  • Clevenger, Caroline M
  • Monghasemi, Shahryar
• Publication Date: 2024-9

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; References; Tables;
• Pagination: 38p

Subject/Index Terms

• TRT Terms: Condition surveys; Data collection; Maintenance management; Mixed integer programming; Pavement maintenance; Real time information; Sensors
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Pavements; Planning and Forecasting;

Filing Info

• Accession Number: 01941297
• Record Type: Publication
• Report/Paper Numbers: MPC-612, MPC-24-565
• Files: UTC, NTL, TRIS, USDOT
• Created Date: Dec 30 2024 9:58AM