Obtaining Reliable Pavement Friction Measurements Using Connected Vehicles
Pavement friction is a critical factor influencing vehicle control and stopping distance, particularly under wet conditions, yet current measurement practices rely on infrequent and labor-intensive testing methods. These limitations prevent agencies from identifying hazardous low-friction locations in a timely manner. This project investigates whether connected vehicle sensor data can provide a reliable and continuous alternative for pavement friction monitoring. The research will validate friction estimates derived from connected passenger vehicles against locked-wheel skid testing and invasive and non-invasive roadway sensors. Data will be collected on multiple pavement types along a test corridor in Massachusetts and analyzed using statistical and machine learning methods to relate vehicle-based friction values to standard skid numbers. The project will develop conversion models and data-integration techniques to enable agencies to incorporate connected vehicle friction data into pavement and safety management systems, supporting proactive maintenance and improved roadway safety.
Language
- English
Project
- Status: Active
- Funding: $140,000.00
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Contract Numbers:
69A3552348301
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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:
University of Massachusetts, Amherst
Department of Civil and Environmental Engineering
130 Natural Resources Road
Amherst, MA United States 01003 -
Performing Organizations:
University of Massachusetts, Amherst
Department of Civil and Environmental Engineering
130 Natural Resources Road
Amherst, MA United States 01003 -
Principal Investigators:
Okte, Egemen
Mogawer, Walaa
- Start Date: 20260101
- Expected Completion Date: 20261231
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Subprogram: University Transportation Centers
Subject/Index Terms
- TRT Terms: Connected vehicles; Data fusion; Friction; Machine learning; Pavement surface course; Statistical analysis
- Geographic Terms: Massachusetts
- Subject Areas: Data and Information Technology; Maintenance and Preservation; Pavements; Vehicles and Equipment;
Filing Info
- Accession Number: 01974417
- Record Type: Research project
- Source Agency: New England University Transportation Center
- Contract Numbers: 69A3552348301
- Files: UTC, RIP
- Created Date: Dec 18 2025 3:09PM