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Implementation of Artificial Intelligence to Improve Winter Maintenance

File Language:
English


Details

  • Corporate Creators:
    Exploratory Advanced Research Program (U.S.)
  • Contributors:
    Kessler, Morgan
  • Corporate Contributors:
    United States. Federal Highway Administration
  • Subject/TRT Terms:
  • Publication/ Report Number:
    FHWA-HRT-21-090
  • Resource Type:
    Brief
  • Geographical Coverage:
    United States
  • Corporate Publisher:
    United States. Federal Highway Administration
  • Abstract:
    The union of technology and transportation is leading to advancements in how decisions are made and deployed for winter maintenance activities. Federal Highway Administration (FHWA) is investigating the use of artificial intelligence (AI) to collect and analyze data that could dramatically improve winter maintenance operations, safety, and mobility, as well as reduce costs and labor hours and enhance pavement design and management. Data-Driven MDSS (Dr. MDSS) looks to AI to provide next-level analysis of real-world situations in real time, addressing the risks and challenges of conducting onsite assessments. Dr. MDSS is a type of MDSS that focuses on the access to and handling of internal and external data to make decisions. FHWA’s Exploratory Advanced Research (EAR) Program is supporting research on the potential development of a Dr. MDSS prototype for State departments of transportation (DOTs). Researchers from the Michigan Technological Institute are conducting the research project, "Autonomous Winter Road Maintenance Decision Making Enabled by Boosting Existing Transportation Data Infrastructure with Deep and Reinforcement Learning."
  • Format:
    PDF
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:25f0834fe54e9b517b6a5ce51caeda201f7946a8c70a5aef40d332ebb26bb514b4026c443518bf5407dc4df5b064d92099b72ed1b14cf18745570ae0936bc126
  • Download URL:
  • File Type:
    Filetype[PDF - 1.74 MB ]
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