Correlating Pavement Conditions and Traffic Accidents through AI-based Data Mining

Pavement surface conditions have a strong positive effect on accident risks. Pavement surface distresses directly affect ride comfort and indirectly cause distraction to the driver resulting in loss of control of the vehicle, which may lead to injuries or deaths. The reason for the lack of research on contribution of bad pavement condition to traffic crashes maybe lies in the fact that previously the data of pavement condition are not readily available to researchers in traffic safety, or sometimes it is comparatively hard for researchers to get the systematic data of pavement condition to conduct analyses. The proposed research will take opportunity of current well-known databases such as the long-term pavement performance (LTPP) database and pavement management system (PMS) at state agencies, to conduct deep and systematic data mining on the existing pavement performance and traffic safety data using data-driven intelligence technologies, and develop predictive models in terms of pavement performance, material properties, traffic effects, and pavement maintenance plans. The research outcome will help guide highway agencies to better design, maintain, and manage pavement infrastructures with enhanced roadway safety.

Language

• English

Project

• Status: Active
• Funding: $160,000.84
• 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:

  Mid-America Transportation Center

  University of Nebraska-Lincoln
  2200 Vine Street, PO Box 830851
  Lincoln, NE  United States  68583-0851
• Project Managers:

  Stearns, Amy

• Performing Organizations:

  Missouri University of Science & Technology, Rolla

  Department of Engineering
  202 University Center
  Rolla, MO    65409
• Principal Investigators:

  Liu, Jenny

• Start Date: 20240601
• Expected Completion Date: 20260630
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Artificial intelligence; Data mining; Pavement condition; Pavement design; Pavement maintenance; Pavement management systems; Pavement performance
• Subject Areas: Data and Information Technology; Highways; Materials; Pavements;

Filing Info

• Accession Number: 01972417
• Record Type: Research project
• Source Agency: Mid-America Transportation Center
• Files: UTC, RIP
• Created Date: Nov 21 2025 2:09PM