Artificial Intelligence (AI) for Intelligence Transportation Systems (ITS) Challenges and Potential Solutions, Insights, and Lessons Learned

Details

• Creators:
  Vasudevan, Meenakshy ; Townsend, Haley ; Samach, Matt ; Walsh, Patrick T. ; Wang, Peiwei ; Seshadri, Anand ; McManus, Ian
• Corporate Creators:
  Noblis, Inc.
• Corporate Contributors:
  United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Artificial intelligence
  • Detection and identification technologies
  • State of the practice
  • Lessons learned
  • Machine learning
  • Statistical bias
  • Data privacy
  • Ethics
  • Liability
  • Generalization
  More +
• Publication/ Report Number:
  FHWA-JPO-22-968
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final
• Contracting Officer:
  Sheehan, Robert; Walker, Jonathan
• Corporate Publisher:
  United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
• Abstract:
  Artificial Intelligence (AI), including Machine Learning (ML), offers the opportunity to make transportation systems safer, and more equitable, reliable, accessible, secure, efficient, and resilient. However, several challenges exist that could impede the successful adoption of AI for Intelligent Transportation Systems (ITS) and the potential realization of these benefits.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/66971/dot_66971_DS1.pdf
• File Type:
  [PDF - 1.97 MB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; Federal Highway Administration ; ITSJPO Digital Library
• Main Document Checksum:
  urn:sha-512:48738b04b044e3993582af99ddbb1da3027c806b90c5ed284562b2c52ac524be93b23ea9447df1d6607df37d9423b8d01d0129542988b3a931c951676cd2eefe