Artificial Intelligence In Transportation Committee

About the committee

• Objectives

  Knowledge Exchange

  To serve as a forum for ideas and knowledge exchange among researchers, engineers, and operators from academia, industry, and government with interests in developing and promoting Artificial Intelligence (AI) technologies and their applications in transportation

  Effort Consolidation

  To serve as a platform for consolidating on-going efforts in academia, industry, and government to form a collective voice and make significant impacts on the development of AI in transportation from the perspectives of both scientific and technological innovations.

  Collaboration

  To serve as a connecter for bridging strengths in academia, industry, and government to promote AI technology transformation, regulation development, and deployment in transportation.

• Needs

  Artificial Intelligence — generally referring to methodologies such as knowledge-based systems, neural networks, clustering, fuzzy sets theory, deep learning, and natural language processing—has already been successfully applied in a variety of areas, including health care, manufacturing, power systems, homeland security, and transportation.

  Both public (NSF, US DOT FHWA, Vople Center, Nevada State DOT, universities, etc.) and private (Microsoft, Toyota, etc.) stakeholders have investigated the potential of AI for civil and transportation applications, including transportation system identification and function approximation, transportation system behavior prediction (i.e., traffic demand, infrastructure deterioration), signal control, traffic pattern recognition, driver classification, traffic accident prediction and detection, route navigation, and self-driving.

  Considering the rapid advances that are being made in adopting and deploying AI-based technology and capabilities into transportation systems, it is important to increase awareness within the transportation community to understand their unique challenges. This will help further advance the efficiency and effectiveness of investing in AI technologies, particularly for improving civil and transportation system safety, mobility, and sustainability.

• Missions

  • Track advancements in AI technology and evaluate their potential impacts on transportation development, policy, research and practice.
  • Foster collaborations between AI technology developers and transportation researchers, agencies, and private sector vendors.
  • Advance AI and transportation science and technology in a mutually inspiring way.
  • Gather and disseminate AI application topics, interim research findings, and emerging market needs.

• Current state-of-the-practice and recent development

  I. Existing Relevant Committees/Task Forces

  • TRB ABJ70 Committee on Artificial Intelligence and Advanced Computing Applications
  • TRB ADB30-5 Sub-Committee on Emerging Technologies in Network Modeling
  • TRB ABJ30 Committee on Urban Transportation Data and Information Systems Committee
  • TRB Task Force on Data for Decisions and Performance Measures
  • American Association of State Highway and Transportation Officials (AASHTO) Committee on Data Management and Analytics

  II. Research Initiatives/Survey Reports/Circular

  • November 2019. Whitehouse: 2016–2019 PROGRESS REPORT: ADVANCING ARTIFICIAL INTELLIGENCE R&D
  • January 2007: Transportation Research Circular E-C113: Artificial Intelligence in Transportation Information for Application
  • June 4, 2018. U.S. DOT Under Secretary of Transportation for Policy. Transportation in the Age of Artificial Intelligence and Predictive Analytics- A Volpe Thought Leadership Series
  • U.S. DOT Artificial Intelligence Activities
  • U.S. DOT Artificial Intelligence Research Highlights
  • FHWA: The Role of Artificial Intelligence and Machine Learning in Federally Supported Surface Transportation Initiatives
  • October 9, 2019, NSF, USDA, DHS, VA, DOT Partner to Foster AI Research
  • NSF: National Artificial Intelligence (AI) Research Institutes: Accelerating Research, Transforming Society, and Growing the American Workforce
  • Nevada DOT Shares Grant for AI-based Traffic Project

• Recent activities

  Workshop

  AI Empowered Technology for Vulnerable Road Users

  Presented at the 26^th IEEE International Conference on Intelligent Transportation Systems

  AI and machine learning (ML) have played a significant role in digital transformation and intelligent robotics in transportation. Advances in computer vision have further accelerated the real-time perception and cognition of the environment and improved the safety of roads and mobility. However, the high demand for self-driving has narrowed our focus to in-vehicle technology. “Walking” is one of the most essential activities in daily life, but AI modeling and simulation in vulnerable road users accessibility and wayfinding has been limited. 

  Workshop

  The Frontiers of Artificial Intelligence-Empowered Methods and Solutions to Urban Transportation Challenges

  Phase II: Best Practice, Education, and Workforce Development

  Dec 15, 2022
  Hilton University of Florida Conference Center
  1714 SW 34th St
  Gainesville, FL 32607
  Sponsored by the National Science Foundation

  Synopsis

  With quickly growing quantity and variety of transportation data, artificial intelligence (AI) technologies are revolutionizing transportation research from system management to automated vehicle and infrastructure control. Emerging AI technologies combined with other analytical methods will lead to improved scientific understandings, transformative informed decisions, and innovative, proactive management solutions of urban transportation infrastructure systems (UTIS). In this workshop, researchers from transportation and computer science disciplines will be invited to explore the frontiers of AI-empowered methods, solutions, and workforce development to urban transportation challenges. The workshop aims to identify the tremendous research and education needs and challenges, and further stimulate transformative research in both transportation and AI communities.

  Agenda

  • Welcome/Opening Remarks: Yueyue Fan, NSF CIS Program Director
  • Keynote: Joe Conway, Director for Transportation Workforce Development at FHWA
  • Session Phase II-I: Emerging AI Technology Applications in Transportation Practices
    Moderator: Lili Du, Associate Professor, UF
    Speakers: Lian Ji, Transportation Planner, AECOM; Mecit Cetin, Professor, Old Dominion University; Balaji Yelchuru, Smart Infrastructure and Mobility Solutions Leader, Accenture; Emmanuel Posadas, PE, Traffic Operations Manager, City of Gainesville
  • Session Phase II-II: AI Technology Training Program Development
    Moderator: Scott Washburn, Professor, UF
    Speakers: Alina Zare, Professor, Associate Dean of HWCOE, Professor of ECE, University of Florida; Mo Malakoutian, Sr. Program Manager at Amazon; Natarajan Janarthanan, Manager, Travel Data, Modeling, and Analysis Office, WSDOT; Heng Wei, Professor, University of Cincinnati
  • Poster Video and Presentation Session
  • Session Phase II-III: New Generation Workforce Development for AI-empowered UTIS
    Moderator: Heng Wei, Professor, University of Cincinnati Speakers: David Kuehn, Program Manager, FHWA; Muhammad Amer, Managing Director, T&DI, ASCE; Larry Rilett, Director of the Auburn University Transportation Research Institute; Ahmed Abdul-Rahim, Professor at the University of ldaho
  • Session Phase II-IV: Roundtable Discussions: Gains and Lessons from Existing Practices and Identify Future Direction
    Group Leaders: Ors. Zhaomiao Guo, Yan Wang, Xianfeng Yang
  • Flash Presentation (3 minutes per presentation, open to all workshop attendees, focusing on gaps of AI implementation, workforce, and education)
  • Discussion Reporting and Closing Remarks

  Organizing Committee

  • Yinhai Wang, Ph.D. (Chair), University of Washington
  • Lili Du, Ph.D. (Chair) - University of Florida
  • Hani Mahmassani, Ph.D., Northwestern University
  • Xianfeng Yang, Ph.D., University of Maryland, College Park
  • Yaw Adu-Gyamfi, Ph.D., University of Missouri
  • Osama Osman, Ph.D., Leidos Inc.
  • Samiul Hasan, Ph.D., University of Central Florida
  • Zhe Jiang, Ph.D. - University of Florida
  • Simon Du, Ph.D. - University of Washington

  Organized by

  • ASCE T&DI Artificial Intelligence in Transportation Committee
  • TRB AED50 Artificial Intelligence and Advanced Computing Applications Committee
  • TRB AEP40-4 Emerging Technologies in Network Modeling Subcommittee
  • TRB AEP40 Committee on Network Modeling
  • Paul G. Allen School of Computer Science & Engr.
  • University of Washington
  • Pacific Northwest Transportation Consortium (PacTrans)
  • University of Florida
  • Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)

  Supporting documents

  NSF_WorkshopFlyer_Dev-15-2022