Automating Variable Speed Limits Using Weather, Traffic and Friction Data

Variable speed limits (VSLs) are useful in promoting highway safety. Along these lines, the Federal Highway Administration (FHWA) mentions, “the use of VSLs during inclement weather or other less than ideal conditions can improve safety by decreasing the risks associated with traveling at speeds that are higher than appropriate for the conditions.” The goal of this proposal is to automatically recommend speeds for various weather conditions (rainfall, snow, ice, fog, etc.) at roadway segments that are good candidates for VSL. This means that the roadway segments should frequently experience adverse weather conditions (such as snow, rain, fog, etc.), high traffic, or safety hazards. The crash rate at such road segments should generally be higher than average. The research team expects to gather road weather information system (RWIS), traffic, friction, incident, and potentially other data sets over one or more seasons that typically exhibit adverse weather. The team will then utilize the collected data and develop analysis methodology in establishing VSL algorithms that consider different terrain types, roadway geometries, and weather conditions (rainfall, snow, ice, fog, etc.). The team will explore the usage of machine learning (ML) algorithms and other approaches in establishing VSL. The speed limits will be set to satisfy the driver’s visibility and stopping sight distance requirements and also prevent lateral slippage at curved sections considering the loss of friction due to inclement weather conditions.

• Record URL:
  https://www.pooledfund.org/Details/Study/658
• Record URL:
  https://rip.trb.org/View/1639799
• Record URL:
  https://ideas.iowadot.gov/subdomain/ideas-main/end/node/3499?qmzn=iKFrYf

Language

• English

Project

• Status: Active
• Funding: $275701
• Contract Numbers:

  TPF-5(435)

• Sponsor Organizations:

  Iowa Department of Transportation

  800 Lincoln Way
  Ames, IA  United States  50010
• Managing Organizations:

  Iowa State University, Ames

  Center for Transportation Research and Education
  2711 South Loop Drive, Suite 4700
  Ames, IA  United States  50010-8664
• Project Managers:

  Greenfield Huitt, Tina

• Performing Organizations:

  National Center for Atmospheric Research

  P.O. Box 3000
  Boulder, Colorado  United States  80307
• Principal Investigators:

  Wiener, Gerry

• Start Date: 20230201
• Expected Completion Date: 20250131
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: High risk locations; Machine learning; Variable speed limits; Weather conditions
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01908407
• Record Type: Research project
• Source Agency: Iowa Department of Transportation
• Contract Numbers: TPF-5(435)
• Files: RIP, STATEDOT
• Created Date: Feb 19 2024 6:55PM