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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 461 - 480 of 613 results
  • Work Zone Safety III: Calibration of Safety Notifications through Reinforcement Learning and Eye Tracking [Supporting Dataset]
    Ergan, Semiha ;
    Ozbay, Kaan
    2022-06-26 | BIN
    Despite increased regulations, restrictive measures, and devices used for warnings, work zone injuries and fatalities are still observed at highway construction projects with alarms/notifications being ignored. With a vision to reduce the number of injuries and fatalities, Phase 3 of the research team's worker safety project extends the original sc ...
    Dataset Supporting Files
  • Improving Methods to Measure Attentiveness through Driver Monitoring [Supporting Dataset]
    Miller, Marty ;
    Herbers, Eileen
    2022-06-24 | BIN
    Driver inattention poses a significant problem on today's roadways, increasing risk for all road users. This report details our efforts in developing algorithms to detect driver inattention. A benchmark dataset was developed based on video review of driving events. Buffer-based algorithms were developed and compared using this benchmark dataset. Th ...
    Dataset
  • Development of AIBased and ControlBased Systems for Safe and Efficient Operations of Connected and Autonomous Vehicles
    Development of AI-Based and Control-Based Systems for Safe and Efficient Operations of Connected and Autonomous Vehicles
    Dong, Jiqian ;
    Du, Runjia
    2022-06-01 | PDF
    Autonomous vehicles (AVs) are an emerging theme for future transportation. However, research on pedestrian-AV interaction, which promotes pedestrian safety during autonomous driving, is not a well-explored domain. One challenge preventing the development of pedestrian-AV interaction research is that there is no publicly available and standardized b ...
  • Enhancing the Accuracy of Construction Cost Estimates for Major Lump Sum LS Pay Items and Generating a MoreAccurate List of Pay Items Throughout the Design Development Process
    Enhancing the Accuracy of Construction Cost Estimates for Major Lump Sum (LS) Pay Items and Generating a More-Accurate List of Pay Items Throughout the Design Development Process
    Ashuri, Baabak ;
    Baek, Minsoo
    2022-06-01 | PDF
    State departments of transportation (DOTs) encounter a critical challenge in estimating accurate cost estimates for major lump sum (LS) pay items, such as Traffic Control and Grading Complete, due to incomplete project information during the early stages of project development. To estimate prices for LS pay items, cost estimators and designers in s ...
  • COVID19s Effect on Transportation Developing a Public COVID19 Data Dashboard
    COVID-19's Effect on Transportation: Developing a Public COVID-19 Data Dashboard
    Ozbay, Kaan ;
    Gao, Jingqin
    2022-06-01 | PDF
    The COVID-19 outbreak has dramatically changed travel behavior in cities across the world. With changed travel demand, economic activity, and social-distancing/stay-at-home policies, transportation systems have experienced an unprecedented shift in demand and usage. Since the start of the pandemic, the C2SMART research team has been collecting data ...
  • Bigdata Analytics and Artificial Intelligence for Smart Intersections
    Bigdata Analytics and Artificial Intelligence for Smart Intersections
    Banerjee, Tania ;
    Chen, Ke
    2022-06-01 | PDF
    This project aims to develop a multi-sensor system for vehicle and pedestrian traffic analysis at traffic intersections. The techniques developed as part of this project are used to process data streams from video-camera and LIDAR systems installed at traffic intersections (along with the loop detector data captured by advanced traffic controllers) ...
  • Deep Learning for Unmonitored Water Level Prediction and Risk Assessment
    Deep Learning for Unmonitored Water Level Prediction and Risk Assessment
    Corns, Steven M ;
    Long, Suzanna K
    2022-06-01 | PDF
    The research uses publicly available data to develop deep learning models to predict river gauge heights at unmonitored locations in Missouri. The geospatial and rainfall data for 20 different catchment areas of Missouri is used in tandem with the clustering and ensemble deep learning approaches to develop a high-performance deep learning model tha ...
  • Large Network MultiLevel Control for CAV and Smart Infrastructure AIBased FogCloud Collaboration
    Large Network Multi-Level Control for CAV and Smart Infrastructure: AI-Based Fog-Cloud Collaboration
    Du, Runjia ;
    Ha, Paul (Young Joun)
    2022-06-01 | PDF
    The first part of this study addresses the use of fog-cloud architecture for a deep reinforcement learning-based control framework and presents a case study involving urban traffic dynamic rerouting. Past work has shown that dynamic rerouting can mitigate traffic congestion and can be facilitated using emerging technologies such as Deep Reinforceme ...
  • Informing Predictions From Above With Data From Below An AIDriven Seismic Ground Failure Model for Rapid Response and Scenario Planning
    Informing Predictions From Above With Data From Below: An AI-Driven Seismic Ground Failure Model for Rapid Response and Scenario Planning
    Maurer, Brett W
    ORCID ICON IMG
    2022-06-01 | PDF
    Geospatial models for predicting soil liquefaction infer subsurface traits via satellite remote sensing and mapped information, rather than directly measure them with subsurface tests. This project developed geospatial models that are driven by algorithmic learning but pinned to a physical framework, thereby benefiting from both machine and deep le ...
  • Rotorcraft Landing Sites Identification Scaling and Generalization of the AI Model
    Rotorcraft Landing Sites Identification - Scaling and Generalization of the AI Model
    Rasool, Ghulam ;
    Bouaynaya, Nidhal
    2022-06-01 | PDF
    The updated information about the location and type of landing sites is essential for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). However, the acquisition, verification, and regular updating of information about landing sites are not straightforward. The lack of current and correct information on helicopter ...
  • Realtime Recommendations for Traffic Control in an Intelligent Transportation System ITS During an Emergency Evacuation Phase II Studies
    Real-time Recommendations for Traffic Control in an Intelligent Transportation System (ITS) During an Emergency Evacuation: Phase II Studies
    Qu, Xiuli ;
    Davis, Lauren
    2022-06-01 | PDF
    Recent hurricanes caused mass evacuations and brought the public attention to the issues occurring during these mass evacuations. To address these issues, the project team has investigated significant cues for hurricane evacuation planners' decisions, built the Rule-based Lens Model (RLM) using Monte-Carlo simulation and supervised machine learning ...
  • MultiAgent Reinforcement LearningBased Pedestrian Dynamics Models for Emergency Evacuation
    Multi-Agent Reinforcement Learning-Based Pedestrian Dynamics Models for Emergency Evacuation
    Park, Hyoshin ;
    Liu, Dahai
    2022-06-01 | PDF
    An efficient and safe evacuation of passengers is important during emergencies. Overcapacity on a route can cause an increased evacuation time. Decision making is essential to optimally guide and distribute pedestrians to multiple routes while ensuring safety. Developing an optimal pedestrian path planning route while considering learning dynamics ...
  • Using Big Data and Machine Learning To Evaluate and Rank the Performance of Traffic Signals in Tennessee
    Using Big Data and Machine Learning To Evaluate and Rank the Performance of Traffic Signals in Tennessee
    Miao, Lei ;
    Meleby, Piro
    2022-06-01 | PDF
    Transportation agencies are tasked with making decisions and taking actions to fight congestion and improve road conditions using the methods and resources available to them. Performance evaluations of traffic conditions at signalized intersections and arterials provide practical data for the agencies to make well-informed decisions for targeted re ...
  • A Hybrid Platform for Context-Aware V2X Communication [supporting datasets]
    Hefeida, Mohamed
    2022-05-04 | PDF
    This report presents a new paradigm for Mobile Edge Learning ("MEL") that enables the implementation of realistic distributed machine learning (DML) tasks on wireless edge nodes while taking into consideration heterogeneous computing and networking environments. A heterogeneity aware (HA) scheme was designed to solve the problem of dynamic task all ...
    Dataset Supporting Files
  • Rotorcraft Landing Sites - An AI-Based Identification System [supporting datasets]
    Rasool, Ghulam ;
    Bouaynaya, Nidhal
    2022-05-02 | PDF
    Location data about U.S. heliports is often inaccurate or nonexistent in the FAA's databases, which leaves pilots and air ambulance operators with erroneous information about where to find safe landing zones. In the 2018 FAA Reauthorization Act, Congress required the FAA to collect better information from the helicopter industry under part 157, whi ...
    Dataset Supporting Files
  • Feasibility Analysis of Realtime Intersection Data Collection and Processing Using Drones Summary
    Feasibility Analysis of Real-time Intersection Data Collection and Processing Using Drones [Summary]
    Ozguven, Eren
    2022-05-01 | PDF
    Florida State University researchers examined the feasibility of extracting detailed intersection traffic data from drone videos using computer vision applications.
  • Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee
    Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee
    Khattak, Asad ;
    Mahdinia, Iman
    2022-05-01 | PDF
    Sponsored by the Tennessee Department of Transportation, this project aims to assist the State of Tennessee prepare for future intelligent mobility strategies that encompass connected and automated vehicles, electric vehicles, multimodal personal and freight movements, all done in a safe, secure, and equitable way. The project has developed a serie ...
  • Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee Part 5 A Comprehensive View of Intelligent Mobility in Tennessee
    Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee - Part 5: A Comprehensive View of Intelligent Mobility in Tennessee
    Khattak, Asad ;
    Mahdinia, Iman
    2022-05-01 | PDF
    Transportation innovations captured through intelligent mobility strategies are critical to achieving economic development, safety, mobility, energy, environmental, and equity goals. Intelligent mobility is broadly defined to encompass connected and automated vehicles, electric vehicles, and multi-modal personal and freight movements, all done safe ...
  • Development of DroneAssisted Highway Mowing Operations Planning Monitoring and Verification Capabilities
    Development of Drone-Assisted Highway Mowing Operations Planning, Monitoring, and Verification Capabilities
    Irizarry, Javier ;
    Cho, Yong Kwon
    2022-05-01 | PDF
    This project focused on the development for the integration of unmanned aerial systems (UASs) and artificial intelligence (AI) to automate planning, monitoring, and performance verification of highway maintenance tasks within the Georgia Department of Transportation (GDOT). The current mowing assessment for verifying the performance of mowing contr ...
  • Drones and Other Technologies To Assist in Disaster Relief Efforts
    Drones and Other Technologies To Assist in Disaster Relief Efforts
    Li, Shuai ;
    Moslehy, Amirsalar
    2022-05-01 | PDF
    Tennessee faces many threats from natural disasters such as storm, flooding, landslide, and earthquake, which damage civil infrastructure and cause major service interruptions. The application of emerging technologies such as drones, sensing technologies, machine learning methods, and optimization techniques in disaster preparedness, response, and ...
461 - 480 / 613
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