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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 61 - 80 of 613 results
  • A Dynamic Analysis of the Built EnvironmentTravel Behavior Relationship Using Three ActivityTravel Surveys in the Austin Texas Region
    A Dynamic Analysis of the Built Environment-Travel Behavior Relationship Using Three Activity-Travel Surveys in the Austin, Texas Region
    Zhang, Ming ;
    Zafri, Niaz
    2025-11-01 | PDF
    This study investigates the dynamic effects of the built environment on travel in Austin, Texas, over a 20-year period. Using three waves of household travel surveys from 1997, 2006, and 2017, the research employs a repeated cross-sectional approach to address the limitations of traditional longitudinal and cross-sectional studies, and to more accu ...
  • Optimizing the Planning of Precast Concrete Bridge Construction Methods to Maximize Durability, Safety, and Sustainability [supporting dataset]
    El-Rayes, Khaled ;
    Ignacio, Ernest-John
    2025-11-01 | ZIP
    The main goal of this project is to provide DOT planners with much-needed support that enables them to analyze and compare the performance of alternative bridge construction methods during the early design phase and optimize their construction decisions during the preconstruction phase. To accomplish this goal, the main tasks of this project focuse ...
    Dataset Supporting Files
  • Remote Bridge Health Monitoring for Scouring Using CostEfficient Sensing Technology
    Remote Bridge Health Monitoring for Scouring Using Cost-Efficient Sensing Technology
    Yee, Tien ;
    Yang, Jidong J.
    2025-11-01 | PDF
    Bridge scour is a leading cause of hydraulic-related bridge failures, yet current monitoring practices rely on periodic inspections that are insufficient during floods when scour activity accelerates. To address this gap, a low-cost (under $1,000 per unit) remote scour-monitoring system was developed and deployed on two scour critical bridges in Ge ...
  • Augmented Information in the Driving Environment Increasing Pedestrian Safety with Augmented Reality Indicators for Older Adult Drivers in Maine
    Augmented Information in the Driving Environment: Increasing Pedestrian Safety with Augmented Reality Indicators for Older Adult Drivers in Maine
    Brown, Justin R. ;
    Fink, Paul D. S.
    2025-10-31 | PDF
    This report describes the project activities conducted at The University of Maine's VEMI Lab to address the increasing rate of vehicle-pedestrian collisions within the state of Maine and to improve older adult driving safety. Leveraging VEMI's experience with virtual reality environments, human-subject research, and the lab's fully immersive autono ...
  • Safer Faster Smarter Pairing CloudBased Vehicle Preemption and AI Intersection Video Analytics data management plan
    Safer, Faster, Smarter: Pairing Cloud-Based Vehicle Preemption and AI Intersection Video Analytics [data management plan]
    Karanikolas, Christina
    ORCID ICON IMG
    2025-10-28 | PDF
    RTC's Safer, Smarter, Faster smart technology traffic signal project utilized a cloud-based signal timing optimization system that supports transit signal priority (TSP) and enhances safety using artificial intelligence intersection analytics (AIA). The limits for Stage 1 pilot project encompass UMC hospital and downtown Las Vegas. Intersection ana ...
  • Enhancing the Durability of Bridge Decks by Incorporating Microencapsulated Phase Change Materials PCMs in Concrete
    Enhancing the Durability of Bridge Decks by Incorporating Microencapsulated Phase Change Materials (PCMs) in Concrete
    Paswan, Rakesh ;
    Li, He-Wen-Xuan
    2025-10-17 | PDF
    In cold climate regions, repeated freezing and thawing during the winter months causes concrete on bridges and road surfaces to crack and deteriorate over time. This damage shortens the service life of transportation infrastructure and increases maintenance costs. To address this problem, this project explored the use of microencapsulated phase cha ...
  • Machine Learning Based Analysis of Activity Patterns to Assess Travel Behavior in Five Boroughs of New York City
    Machine Learning Based Analysis of Activity Patterns to Assess Travel Behavior in Five Boroughs of New York City
    Allahviranloo, Mahdieh ;
    Kannam, Nikhita
    2025-10-03 | PDF
    This study examines changes in urban mobility patterns in New York City between 2019 and 2022 using machine learning techniques. Analysis of the Citywide Mobility Survey data (n=85,000) reveals a reduction from seven distinct activity clusters in 2019 to four in 2022. We implement three machine learning approaches - Decision Trees, Random Forest, a ...
  • Safer, Faster, Smarter: Pairing Cloud-Based Vehicle Preemption and AI Intersection Video Analytics [supporting dataset]
    Karanikolas, Christina
    ORCID ICON IMG
    2025-10-01 | ZIP
    RTC's Safer, Smarter, Faster smart technology traffic signal project utilized a cloud-based signal timing optimization system that supports transit signal priority (TSP) and enhances safety using artificial intelligence intersection analytics (AIA). The limits for Stage 1 pilot project encompass UMC hospital and downtown Las Vegas. Intersection ana ...
    Dataset
  • Career Opportunities in Intelligent Transportation Systems ITS
    Career Opportunities in Intelligent Transportation Systems (ITS)
    Grahn, Rick ;
    Silverstein, Claire
    2025-10-01 | PDF
    Intelligent Transportation Systems (ITS) offer a powerful, cost-effective approach to improving roadway safety and efficiency, especially when traditional infrastructure expansion is either impractical or fails to meet longer-term needs. Their ability to address complex challenges are driving substantial growth in the ITS field as transportation sy ...
  • 319 Detection and Monitoring of Material Aging and Structural Deterioration Using Electromagnetic and Mechanical Sensors with Virtual Reality and Machine Learning Modeling
    3.19 Detection and Monitoring of Material Aging and Structural Deterioration Using Electromagnetic and Mechanical Sensors with Virtual Reality and Machine Learning Modeling
    Yu, Tzuyang ;
    Wei, Jianqiang
    2025-09-30 | PDF
    The research problem we are trying to solve is the detection and monitoring of aging civil infrastructure components and systems in New England by using visual information and subsurface images in a virtual reality (VR) environment for data visualization and machine learning (ML) for data interpretation. The overall research objective is to study t ...
  • Enhanced Datasets and AI Models for Monitoring of Grade Crossings
    Enhanced Datasets and AI Models for Monitoring of Grade Crossings
    Ali, Gasser ;
    Tarawneh, Constantine
    2025-09-30 | PDF
    Safety at grade crossings is a major concern due to the number of accidents every year. Many innovative technologies have been proposed to automate the monitoring of crossings. The goal of this research is to investigate the use of Artificial Intelligence (AI) and Deep Learning (DL) to monitor grade crossings and detect various hazardous conditions ...
  • Towards Building a Foundation AI Model for Railway Safety
    Towards Building a Foundation AI Model for Railway Safety
    Papalexakis, Evangelos ;
    Chen, Jia
    2025-09-30 | PDF
    Large language models (often also termed foundation models) are revolutionizing multiple aspects of every-day life and work, with the use of artificial intelligence (AI) agents like ChatGPT being now commonplace and transforming life, work, and scientific discovery as we know it. In this project, we harness the power of such foundation models in or ...
  • Deep Learning with LiDAR Point Cloud Data for Automatic Roadway Health Monitoring
    Deep Learning with LiDAR Point Cloud Data for Automatic Roadway Health Monitoring
    Trinidad, Rafael ;
    Sherafat, Ardavan
    2025-09-25 | PDF
    Maintaining roadway safety requires accurate monitoring of both pavement conditions and traffic sign infrastructure. Traditional methods, such as manual inspection or LiDAR-based systems, are costly, time-consuming, and difficult to scale. This work introduces a cost-effective, image-based framework that leverages dense 3D point cloud data, geometr ...
  • RIDERS: Real-Time Information Dissemination for Efficiency in a Robo-Taxi System [supporting dataset]
    Filipovska, Monika ;
    Bala, Haimanti
    2025-09-15 | PDF
    Real-time traffic information is critical for efficient robo-taxi fleet management, yet such data is often costly to obtain and incomplete in mixed traffic with low autonomous vehicle (AV) penetration. This project addresses this challenge by proposing a hierarchical reinforcement learning (HRL) framework that enables fleets to act not only as mobi ...
    Dataset Supporting Files
  • Analyzing NPMRDS Using Advanced Machine Learning to Enhance Road Safety Public Health and System Performance
    Analyzing NPMRDS Using Advanced Machine Learning to Enhance Road Safety, Public Health and System Performance
    Faezipour, Miad ;
    Park, Sangho
    2025-09-12 | PDF
    This project aims to leverage NPMRDS data and machine learning techniques to analyze the relationships between speed variations, crash occurrences, weather conditions, and road geometry. The goal is to identify patterns that can measure the performance of road segments and inform targeted safety interventions and infrastructure improvements. The pr ...
  • Data for: Deep Learning Based Automated Data Collection Technology for Coastal Highway Pavements [supporting data]
    Wang, Feng ;
    Sanchez, Carlos
    2025-09-11 | JSON
    Tables and graphs for deep learning model performance not used in the Coastal REsearch And Transportation Education (CREATE) Report for Deep Learning Based Automated Data Collection Technology for Coastal Highway Pavements. These include performance metrics such as precision, recall, and mean average precision at 50% overlap (mAP50) for each model ...
    Dataset Supporting Files
  • AIEnabled Vision System for Intersection Analytics
    AI-Enabled Vision System for Intersection Analytics
    Adu-Gyamfi, Yaw ;
    Tanner, Muturi
    2025-09-01 | PDF
    This project developed and demonstrated an AI-enabled vision system for intersection analytics capable of automatically generating Turning Movement Counts (TMCs) and integrating them with Signal Phase and Timing (SPaT) data to evaluate traffic signal performance. Using existing Missouri Department of Transportation (MoDOT) CCTV (Closed Circuit Tele ...
  • AIEnabled Vision System for Intersection Analytics Research Summary
    AI-Enabled Vision System for Intersection Analytics [Research Summary]
    Adu-Gyamfi, Yaw ;
    Schulte, Brent
    2025-09-01 | PDF
    This project is designed to overcome the challenges faced by today's traffic management systems by: 1. Developing a fully automated vision system architecture to generate Turning Movement Counts (TMCs) eliminating the need for manual directional inputs. 2. Integrating TMCs with SPaT data to generate key intersection performance metrics including de ...
  • A Pilot Experimental Project for Predicting Pedestrian Flows Using Computer Vision and Deep Learning
    A Pilot Experimental Project for Predicting Pedestrian Flows Using Computer Vision and Deep Learning
    Han, Chaeyeon ;
    Chivilkar, Shreya
    2025-09-01 | PDF
    This study presents a pilot project for predicting pedestrian flows using video-based computer vision and deep learning techniques. Two custom datasets were collected on the Georgia Tech campus, featuring video recordings of multiple pedestrian pathways along with annotated pedestrian counts and directional flow information. A methodological framew ...
  • EndtoEnd Learning Framework for Transportation Network Equilibrium Modeling
    End-to-End Learning Framework for Transportation Network Equilibrium Modeling
    Liu, Zhichen ;
    Yin, Yafeng
    2025-09-01 | PDF
    This project introduces an end-to-end framework for constructing integrated traffic network equilibrium models, which can serve as lightweight travel demand models, directly from multi-day aggregate traffic state observations. Unknown components on both the supply and demand sides are parameterized with computational graphs and embedded in a variat ...
61 - 80 / 613
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