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Artificial Intelligence Deployment Center of Excellence (AI COE)

rosaP Repository & Open Science Access Portal

The AI COE Collection is a central resource for transportation stakeholders that may aid in deployment of safe and responsible AI in surface transportation. The collection will feature current and emerging resources, innovations, and technologies. For more information on the AI COE, go to https://highways.dot.gov/ai-coe.

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Showing 1 - 10 of 10 results
  • MultiDimensional TimeBased Track Safety and Quality Index in Support of Autonomous Track Geometry Inspection
    Multi-Dimensional Time-Based Track Safety and Quality Index in Support of Autonomous Track Geometry Inspection
    Palese, Joseph W. ;
    Zarembski, Allan M.
    2026-07-01 | PDF
    In this research, the Federal Railroad Administration (FRA) sponsored a team from the University of Delaware to develop a multidimensional, time-based Track Safety and Quality Index (TSQI) for assessing and monitoring the condition of railway tracks. The index captures the temporal dependencies and uncertainties associated with track parameters by ...
  • Development of an MLBased Georgia Pavement Structural Condition Evaluation System
    Development of an ML-Based Georgia Pavement Structural Condition Evaluation System
    Tsai, Yichang (James) ;
    Yang, Zhongyu
    2026-07-01 | PDF
    Georgia's aging interstate highway network requires more reliable pavement evaluation to support maintenance and rehabilitation (M&R) planning. Current network-level practices rely primarily on surface condition data, which can lead to project-level cost overruns when structural deficiencies are discovered only after budgets have been defined from ...
  • Evaluation of Steel Bridge Girders Damaged by OverHeight Vehicle Strikes Using Terrestrial Laser Scanning and Machine Learning
    Evaluation of Steel Bridge Girders Damaged by Over-Height Vehicle Strikes Using Terrestrial Laser Scanning and Machine Learning
    Ibrahim, Ahmed E. ;
    Schissler, Limo R.
    2026-07-01 | PDF
    Bridge strikes caused by over-height vehicles frequently damage steel girders and can reduce their load-carrying capacity, requiring rapid and reliable evaluation to ensure structural safety. Current evaluation practices rely on manual measurements that often require traffic disruptions and simplified assessment approaches that do not fully capture ...
  • SMART METRO Implementation Report
    SMART METRO [Implementation Report]
    Broward County Metropolitan Planning Organization (Florida)
    2026-06-02 | PDF
    The Broward Metropolitan Planning Organization (BMPO) will plan, design, and develop a cloud-based digital twin platform prototype to unify regional data across agency and departmental silos. The "SMART METRO" prototype leverages advanced systems integration and artificial intelligence technology to synthesize and analyze transportation, land use, ...
  • Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence
    Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence
    Moomen, Milhan ;
    Meng, Xiangyu
    2026-06-01 | PDF
    Signalized intersections are critical points in urban transportation networks where congestion, delays, and safety risks are most prominent. Traditional approaches for performance evaluation rely on manual field counts, loop detectors, or expensive infrastructure-based systems, which are often limited in accuracy, scalability, and adaptability. Thi ...
  • Development of UASEnabled Bridge Deck Inspection System From Investigation to Implementation
    Development of UAS-Enabled Bridge Deck Inspection System From Investigation to Implementation
    Almasi, Pouya ;
    Zhang, Qianyun
    2026-05-31 | PDF
    We introduce a pilot study that is geared towards inaugurating a UAS-centric bridge inspection program, operating on a component-level approach, with the overarching goal of enhancing the caliber of bridge inspection methodologies within the confines of New Mexico. The envisioned program encompasses the formulation of UAS-based inspection strategie ...
  • Benchmarking Computer VisionBased Approaches To Derive EngineeringOriented Condition From Existing UDOT Assets Data
    Benchmarking Computer Vision-Based Approaches To Derive Engineering-Oriented Condition From Existing UDOT Assets Data
    Pandey, Shailaja Ratna ;
    Esteghamati, Mohsen Zaker
    2026-02-01 | PDF
    Condition assessment of how transportation infrastructure supports safe and reliable road and highway operation. Departments of Transportation across the country rely heavily on manual inspections, which are time-consuming and costly. This study evaluated whether modern computer vision (CV) methods can support traffic sign condition assessment alon ...
  • Creating a Data Science Competition for Intersection Safety Systems Insights from the US DOT Intersection Safety Challenge Stage 1B System Assessment and Virtual Testing
    Creating a Data Science Competition for Intersection Safety Systems - Insights from the U.S. DOT Intersection Safety Challenge Stage 1B System Assessment and Virtual Testing
    Goli, Mohammad ;
    Townsend, Haley
    2026-02-01 | PDF
    To assess the technological maturity of data fusion and artificial intelligence (AI) capabilities of intersection safety systems (ISS), the U.S. DOT designed the Intersection Safety Challenge Stage 1B: System Assessment and Virtual Testing as a data science competition. For this data science competition, the U.S. DOT collected and provided real-wor ...
  • Artificial Intelligence and Its Role and Use Within State DOTs
    Artificial Intelligence and Its Role and Use Within State DOTs
    Egge, Mark ;
    Tate, Syndney
    2026-01-01 | PDF
    Artificial Intelligence (AI) is increasingly shaping the way state Departments of Transportation (DOTs) approach both research and daily operations. This powerful technology creates new opportunities for improving efficiency, supporting decision-making, and streamlining agency workflows, but it also presents new challenges, including concerns about ...
  • Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence Technical Summary
    Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence [Technical Summary]
    Moomen, Milhan ;
    Codjoe, Julius
    2026-01-01 | PDF
    The objective of this project was to develop and evaluate artificial intelligence (AI)-based computer vision tools for intersection performance analysis. The specific objectives were to: • Develop a vehicle counting framework based on detection-tracking-counting pipeline for accurate turn-movement measurements; • Develop an integrated framework for ...
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