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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 281 - 300 of 613 results
  • Pilot Study on Improving Crash Data Accuracy in Kentucky through University Collaboration
    Pilot Study on Improving Crash Data Accuracy in Kentucky through University Collaboration
    Fields, Michael A. ;
    Green, Eric
    2024-02-01 | PDF
    Without high-quality crash data and robust interpretive/analytical tools to analyze these data, transportation agencies will struggle to develop evidence-based strategies for improving road safety. Crash narratives are one element of crash reports that pose especially acute interpretive challenges. These narratives supplement coded data and give an ...
  • Roadway IceSnow Detection using a Novel Infrared Thermography Technology
    Roadway Ice/Snow Detection using a Novel Infrared Thermography Technology
    Zhu, Xuan ;
    He, Xiangdong
    2024-02-01 | PDF
    Safety is a principal concern for highway transportation, and slippery roads can pose high risks for vehicle crashes in snowy regions, which cover about 70% of road networks in the United States. Slippery road conditions can significantly increase the risk of vehicle crashes. Therefore, roadway agency staff find it critical to clear road surfaces i ...
  • Roadway IceSnow Detection using a Novel Infrared Thermography Technology Summary
    Roadway Ice/Snow Detection using a Novel Infrared Thermography Technology [Summary]
    Zhu, Xuan ;
    Yang, Xianfeng
    2024-02-01 | PDF
    Safety is a principal concern for highway transportation, and slippery roads can pose high risks for vehicle crashes in snowy regions, which cover about 70% of road networks in the United States. Slippery road conditions can significantly increase the risk of vehicle crashes. Therefore, roadway agency staff find it critical to clear road surfaces i ...
  • Dynamic Prediction of Shared Micromobility Usage with MultiTask Learning
    Dynamic Prediction of Shared Micromobility Usage with Multi-Task Learning
    Guo, Yujie ;
    Chen, Ying
    2024-01-31 | PDF
    Taxis and Transportation Network Companies (TNCs) are important components of the urban transportation system. An accurate short-term forecast of passenger demand can help operators better allocate taxi or TNC services to achieve supply-demand balance in real time. As a result, drivers can improve the efficiency of passenger pick-ups, thereby reduc ...
  • Development of an Infrastructure Based Data Acquisition System to Naturalistically Collect the Roadway Environment [supporting dataset]
    Sarkar, Abhijit ;
    Papakis, Ioannis
    2024-01-31 | JSON
    Automatic traffic monitoring is becoming an important investment for transportation specialists, especially as the overall volume of traffic continues to increase, as do crashes at intersections. Infrastructure cameras can be a good source of information for automatic monitoring of traffic situations at intersections. However, efficient computer vi ...
    Dataset
  • Rapid and Accurate Assessment of Road Damage by Integrating Data from Mobile Camera Systems MCS and Mobile LiDAR Systems MLS
    Rapid and Accurate Assessment of Road Damage by Integrating Data from Mobile Camera Systems (MCS) and Mobile LiDAR Systems (MLS)
    Chen, Qi
    ORCID ICON IMG
    2024-01-26 | PDF
    In this project, we devised an innovative approach to produce highly detailed orthomosaics of road surfaces, with a spatial resolution as fine as millimeters, utilizing panoramic photos obtained from a mobile camera system combined with Structure-from-Motion technology. Our method emphasizes the necessity of accurately masking out the ego-vehicle ( ...
  • An Exploration of the Use of Artificial Intelligence for Enhanced Traffic Management Operations and Safety
    An Exploration of the Use of Artificial Intelligence for Enhanced Traffic Management, Operations and Safety
    Juri, Natalia Ruiz ;
    Perrine, Ken
    2024-01-24 | PDF
    This project explored the use and value of artificial intelligence and machine learning (ML) in transportation taking a multi-pronged approach that includes a literature review, a workshop, a survey, the development of3 prototype ML models for four high-priority use cases, and the field testing of one of the prototyped models. Initial tasks were ex ...
  • Developing an Intelligent Transportation Management Center (ITMC) With a Safety Evaluation Focus for Smart Cities [supporting dataset]
    Salehipour, Sina ;
    Jahangiri, Arash
    2024-01-19 | JSON
    In the context of smart cities, ensuring transportation safety is a complex task that involves understanding the impact of new technologies, measuring the effectiveness of safety measures, and identifying high-risk locations. However, recent advances in communication and big data analytics have made it possible to address these challenges in a more ...
    Dataset
  • Development of Traffic Video Analysis Tool for Highway Safety Performance Evaluation
    Development of Traffic Video Analysis Tool for Highway Safety Performance Evaluation
    Zhou, Huaguo ;
    Zhao, Zijie
    2024-01-01 | PDF
    Recent advances in computer vision techniques have enabled the use of traffic video data for valuable surrogate safety measures to improve highway safety evaluations. However, few tools specifically target abnormal traffic events like wrong-way driving (WWD) or illegal left turns. This research aims to develop a cost-effective video analytic tool, ...
  • A Preliminary Cost Estimating Model for Transportation Projects
    A Preliminary Cost Estimating Model for Transportation Projects
    Piratla, Kalyan R. ;
    Le, Tuyen
    2024-01-01 | PDF
    As with any state highway agency (SHA), the construction needs exceed the budget limitations, which mandates that SCDOT prioritizes transportation project needs based on benefit/cost considerations. It is important to use every penny as wisely as possible. In such context, an early-stage cost estimate is imperative for evaluating the feasibility of ...
  • Developing an Intelligent Transportation Management Center ITMC With a Safety Evaluation Focus for Smart Cities
    Developing an Intelligent Transportation Management Center (ITMC) With a Safety Evaluation Focus for Smart Cities
    Salehipour, Sina ;
    Jahangiri, Arash
    2024-01-01 | PDF
    In the context of smart cities, ensuring transportation safety is a complex task that involves understanding the impact of new technologies, measuring the effectiveness of safety measures, and identifying high-risk locations. However, recent advances in communication and big data analytics have made it possible to address these challenges in a more ...
  • Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence Research Project Capsule 244SS
    Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence: Research Project Capsule [24-4SS]
    Moomen, Milhan ;
    Rupnow, Tyson
    2024-01-01 | PDF
    The primary objectives of this research are to: • Assess the feasibility and accuracy of using computer vision technology for performance evaluation at signalized intersections. • Provide intersection video footage data captured by drones. • Use computer vision and artificial intelligence to automatically convert data from video recordings at selec ...
  • Machine Learning for Improving Air Mobility Under Emergency Situations
    Machine Learning for Improving Air Mobility Under Emergency Situations
    Liu, Yongxin ;
    Liu, Dahai
    2024-01-01 | PDF
    This project investigates the integration of advanced machine learning and optimization techniques to improve air traffic management during emergencies. Over three phases, the study utilized AI to predict flight delays, optimize evacuation processes, and plan efficient evacuation flight paths, enhancing the resilience of air mobility systems in cri ...
  • Physicsinformed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control
    Physics-informed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control
    Li, Xianning ;
    Wang, Yebin
    2024-01-01 | PDF
    This paper proposes a novel physics-informed machine learning framework for motion planning and control of autonomous vehicles. By integrating longitudinal and lateral control, a nonlinear control problem is formulated using Model Predictive Control (MPC). To address computational challenges, a self-supervised framework, Recurrent Predictive Contro ...
  • Delivering Maintenance and Repair Actions via AutomatedRobotic Systems
    Delivering Maintenance and Repair Actions via Automated/Robotic Systems
    Gong, Jie ;
    Liang, Xiao
    2023-12-31 | PDF
    This study explores the emerging role of robotics in infrastructure inspection and repair. Through a multidisciplinary workshop and a series of proof-of-concept field studies, we evaluated the capabilities of advanced robotic platforms-particularly quadruped systems like Boston Dynamics' SPOT-and AI-powered remote sensing tools. Results showed stro ...
  • Enhancing Automated Vehicle Safety Through Testing with Realistic Driver Models [supporting dataset]
    Garcia, Alfredo ;
    McDonald, Anthony D
    2023-12-07 | JSON
    Driver process models play a central role in the testing, verification, and development of automated and autonomous vehicle technologies. Prior models developed from control theory and physics-based rules are limited in automated vehicle applications due to their restricted behavioral repertoire. Data-driven machine learning models are more capable ...
    Dataset
  • Real-Time Risk Prediction at Signalized Intersection Using Graph Neural Network [supporting dataset]
    Sonth, Akash ;
    Xu, Yanchao
    2023-12-07 | JSON
    Intersection-related traffic crashes and fatalities are major concerns for road safety. This project aimed to understand the major causes of conflicts at intersections by studying the intricate interplay between roadway agents. The approach involved using the current traffic camera systems to automatically process traffic video data. As manual anno ...
    Dataset
  • Automated RealTime Weather Detection System Using Artificial Intelligence
    Automated Real-Time Weather Detection System Using Artificial Intelligence
    Ahmed, Mohamed M ;
    Khan, Md Nasim
    2023-12-01 | PDF
    Adverse weather conditions have long been recognized as a leading contributing factor to motor vehicle crashes, primarily due to their adverse effects on visibility and road surfaces. Providing drivers with real-time weather information is essential to ensure safe driving in adverse weather conditions. Nonetheless, the identification of road weathe ...
  • Current Status of Transportation Data Analytics and Pilot Case Studies Using Artificial Intelligence AI
    Current Status of Transportation Data Analytics and Pilot Case Studies Using Artificial Intelligence (AI)
    Xie, Yuanchang ;
    Liu, Ruifeng
    2023-12-01 | PDF
    Data is becoming increasingly important for state Departments of Transportation (DOTs) in making strategic and day to- day decisions. This research offers a comprehensive review of both existing and emerging data sources for Transportation Systems Management and Operations (TSMO). It discusses and summarizes the pros and cons of each data source. A ...
  • Deep Learning Machine Learning or Statistical Models for WeatherRelated Crash Severity Prediction
    Deep Learning, Machine Learning, or Statistical Models for Weather-Related Crash Severity Prediction
    Ogungbire, Abimbola ;
    Kalambay, Panick
    2023-12-01 | PDF
    Nearly 5,000 people are killed and more than 418,000 are injured in weather-related traffic incidents each year. Assessments of the effectiveness of statistical models applied to crash severity prediction compared to machine learning (ML) and deep learning techniques (DL) help researchers and practitioners know what models are most effective under ...
281 - 300 / 613
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