Real-World AI Scenarios in Transportation for Possible Deployment

Artificial Intelligence (AI) is revolutionizing every walk of life, allowing machines to learn from experience, adapt, and perform tasks that have historically required human cognition. The US government elevated AI as one of its key priority science and technology areas. In response, the Intelligent Transportation Systems (ITS) Joint Program Office (JPO) established research in AI as a priority area to accelerate adoption of AI by state and local agencies for addressing transportation problems. As the US Department of Transportation (USDOT) embarks on advancing AI in transportation, it is essential to focus on high-value scenarios that can be used to motivate and inform stakeholders, accelerate the impact of AI deployment, and form the basis for potential proof of concept tests, prototype demonstrations and deployments that illustrate the transformational power of AI. The purpose of this report is to identify practical real-world scenarios where AI offers the potential to address specific transportation needs. The potential AI applications are identified based on a review of literature and interviews of public and private sector deployers and researchers of AI applications.

• Record URL:
  https://rosap.ntl.bts.gov/view/dot/50752
• Supplemental Notes:
  • Cover title: Identifying Real-World Transportation Applications Using Artificial Intelligence (AI): Real-World AI Scenarios in Transportation for Possible Deployment.
• Corporate Authors:

  Noblis, Incorporated

  500 L’Enfant Plaza, S.W., Suite 900
  Washington, DC  United States  20024

  Department of Transportation

  Intelligent Transportation Systems Joint Program Office
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Vasudevan, Meenakshy
  • Townsend, Haley
  • Schweikert, Edward
  • Wunderlich, Karl
  • Burnier, Carolina
  • Hammit, Britton
  • Gettman, Doug
  • Ozbay, Kaan
• Publication Date: 2020-7

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Illustrations; References;
• Pagination: 101p

Subject/Index Terms

• TRT Terms: Artificial intelligence; Forecasting; Implementation; Intelligent transportation systems; Literature reviews; Stakeholders; Transportation planning
• Subject Areas: Data and Information Technology; Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01754649
• Record Type: Publication
• Report/Paper Numbers: FHWA-JPO-20-810
• Contract Numbers: DTFH61-16-D-00036
• Files: NTL, TRIS, ATRI, USDOT
• Created Date: Oct 14 2020 5:41PM