Developing a Proactive Fuzzy-Logic Model for Optimizing Winter Road Maintenance Measures in Cold Urban Areas Using Real-Time Data

This research introduces a method for comprehensively optimizing winter road maintenance in urban areas where transportation quality can significantly be affected by adverse climatic conditions. The research is expected to provide help with the following: 1) detecting existing gaps in winter road maintenance, 2) maximizing the efficiency of investments in maintaining the quality of transportation during the cold season, and, 3) improving the safety, comfort, and economy of the residents of affected areas.

• Dataset URL:
  https://doi.org/10.7910/DVN/FHGNWV
• Record URL:
  http://hdl.handle.net/1773/49797
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Supporting dataset available at: https://doi.org/10.7910/DVN/FHGNWV
• Corporate Authors:

  Pacific Northwest Transportation Consortium

  University of Washington
  More Hall Room 112
  Seattle, WA  United States  98195-2700

  Office of the Assistant Secretary for Research and Technology

  Department of Transportation
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Tafazzoli, Tommy
  • 0000-0003-4946-3666
• Publication Date: 2022-10-31

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 82p

Subject/Index Terms

• TRT Terms: Highway maintenance; Optimization; Real time information; Urban areas; Winter maintenance
• Subject Areas: Highways; Maintenance and Preservation; Operations and Traffic Management;

Filing Info

• Accession Number: 01882114
• Record Type: Publication
• Report/Paper Numbers: 2020-S-WSU-3
• Contract Numbers: 69A3551747110
• Files: UTC, TRIS, ATRI, USDOT
• Created Date: May 16 2023 4:53PM