Guidelines for AI-based Decision Supporting System (DSS) solutions for State Departments of Transportation (DOT)

Artificial intelligence (AI) is rapidly transforming many industries, and the transportation sector is no exception. AI-based decision support systems (DSS) have the potential to revolutionize the way state departments of transportation (DOTs) manage their transportation networks. AI-based DSS can be used to collect, analyze, and interpret large amounts of data from a variety of sources, such as traffic cameras, sensors, and social media. This information can be used to generate insights and recommendations that can help DOTs make better decisions about everything from traffic management to infrastructure planning. As transportation systems become more complex and demanding, DOTs need tools that can help them to make better decisions more quickly and efficiently. The objective of this research is to develop guidelines for AI-based DSS solutions for DOTs.

• Record URL:
  http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=5690
• Supplemental Notes:
  • Contract to a Performing Organization has not yet been awarded.

Language

• English

Project

• Status: Proposed
• Funding: $400000
• Contract Numbers:

  Project 20-133

• Sponsor Organizations:

  National Cooperative Highway Research Program

  Transportation Research Board
  500 Fifth Street, NW
  Washington, DC  United States  20001

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590

  American Association of State Highway and Transportation Officials (AASHTO)

  444 North Capitol Street, NW
  Washington, DC  United States  20001
• Project Managers:

  Barcena, Roberto

• Start Date: 20240520
• Expected Completion Date: 0
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Artificial intelligence; Data analysis; Data collection; Decision making; Networks; State departments of transportation
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01919352
• Record Type: Research project
• Source Agency: Transportation Research Board
• Contract Numbers: Project 20-133
• Files: TRB, RIP
• Created Date: May 22 2024 2:08PM