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ViewAttendees 5

IPOD Abstract for presentation (Poster or Podium)

Uncrewed Aerial Systems

1666999 - AI-Enhanced Unmanned Aerial Systems for Transportation Safety and Traffic Management

Monday, June 17, 2024
1:30 PM - 1:50 PM ET
Room: 215

    Primary Author(s)

  • Behnam Jamali

    Computer Vision & AI Specialist
    Transoft Solutions
    Montreal, QC, Canada

    • Co-Author(s)

  • Behnam Jamali

    Computer Vision & AI Specialist
    Transoft Solutions
    Montreal, QC, Canada

    • Presenter(s)

  • Behnam Jamali

    Computer Vision & AI Specialist
    Transoft Solutions
    Montreal, QC, Canada

    • Co-Author(s)

  • Karen Giese, P.E.

    Vice President, US Business Development
    Transoft Solutions
    Richmond, BC, Canada

    • Presenter(s)

  • Karen Giese, P.E.

    Vice President, US Business Development
    Transoft Solutions
    Richmond, BC, Canada

    • Submitter(s)

  • BJ

    Behnam Jamali

    Transoft Solutions
    Montreal, Quebec, Canada

Abstract: In an increasingly connected world, the integration of Artificial Intelligence (AI) with Unmanned Aerial Systems (UAS) is leading transformative change in the field of transportation safety and traffic management. AI-powered UAS can efficiently process aerial data to predict, monitor, and respond to traffic patterns, ensuring a seamless traffic flow and substantially reducing on-ground incidents. From enforcing traffic rules, congestion points detection, to anticipating potential collision zones, and facilitating emergency responses, the combination of AI and UAS can offer valuable and accurate insights. However, there are challenges associated with the integration and deployment of these systems, such as data privacy, airspace regulations, and the necessity for a reliable data collection framework. This paper showcases the capabilities of the fusion of AI and UAS in transportation safety and traffic management, while addressing potential issues and obstacles related to these systems. The paper also highlights the adoption of these systems in a few case studies, showing considerable reductions in traffic incidents and improved traffic flow. 

Learning Objectives:

Attendees can expect to learn the following from this session:
  • Understand the video-based road user classification and tracking in Unmanned Aerial Systems aligning with the vehicle classification standard set by the Federal Highway Administration (FHWA)
  • List four main limitations of Unmanned Aerial Systems compared to traditional fixed camera for video-based surrogate safety assessment
  • List three main advantages of Unmanned Aerial Systems compared to traditional fixed camera for video-based surrogate safety assessment