Exploring the Use of Artificial Intelligence to Leverage TxDOT Data for Enhanced Corridor Management and Operations [Project Summary]

Details

• Creators:
  Juri, Natalia Ruiz ; Perrine, Ken ; Boyles, Stephen ; Chin, Kristie ; Gold, Andrea ; Alexander, William ; Avera, Morgan ; Nair, Gopindra S ; Robbennolt, Jake
• Corporate Creators:
  University of Texas at Austin. Center for Transportation Research
• Corporate Contributors:
  Texas. Dept. of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Artificial intelligence
  • Data management
  • Safety
  • Innovation
  • Travel time
  • Information processing
  • Literature reviews
  • Connected vehicles
• Publication/ Report Number:
  0-7034
• Resource Type:
  Brief
• Geographical Coverage:
  Texas ; United States
• Edition:
  Project Summary Report
• Corporate Publisher:
  University of Texas at Austin. Center for Transportation Research
• Abstract:
  This project explored the use and value of AI and ML in transportation taking a multi-pronged approach that includes a literature review, a workshop, a survey, the development of three prototype ML models for four high-priority use cases, and the field testing of one of the prototyped models. Initial tasks were exploratory in nature and led to a better understanding of the current and prospective uses of ML in transportation, corresponding data needs, and specific use cases of interest to TxDOT.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/73573/dot_73573_DS1.pdf
• File Type:
  [PDF - 272.31 KB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:0b2f8ffb58234f2c996f3915d94fb12c349104916695fe530ddfd4293fab147af58c0ca0e76b4fcd464b81e28a14314705dbc5bdd1f8855ec5507709cb86e2ee