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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 261 - 280 of 613 results
  • Impervious Surfaces from High Resolution Aerial Imagery Cities in Fresno County Research Brief
    Impervious Surfaces from High Resolution Aerial Imagery: Cities in Fresno County [Research Brief]
    Ahn, Yushin ;
    Poythress, Richard
    2024-05-01 | PDF
    This research explores the use of various image classification methods on high-resolution aerial imagery to quantify the percentage of urban areas covered by impervious surfaces. Traditional pixel- and object-based classification methods are compared to novel deep learning classification tools.
  • Artificial Intelligence AIEnabled Intelligent Transportation Systems ITS Capability Maturity Model CMM and Readiness Checklists
    Artificial Intelligence (AI)-Enabled Intelligent Transportation Systems (ITS) Capability Maturity Model (CMM) and Readiness Checklists
    Freeman, Brandon ;
    Hadi, Mohammed
    2024-05-01 | PDF
    The United States Department of Transportation (USDOT) recognizes that artificial intelligence (AI) offers benefits in intelligent transportation systems (ITS), such as improving safety, mobility, equity, efficiency, accessibility, productivity, resilience. Several industries use capability maturity models (CMM) to objectively assess an organizatio ...
  • A Machine Learning-Assisted Framework for Determination of Performance Degradation Causes and Selection of Channel Switching Strategy in Vehicular Networks [supporting dataset]
    Huang, Chin Tser ;
    Comert, Gurcan
    2024-04-30 | BIN
    As all three major US mobile carriers have launched their own 5G networks and are working hard to expand their coverage nationwide, 5G has come into everyone's daily life. 5G networks use millimeter-wave (mm-Wave) for higher speeds, while 4G long-term evolution (LTE) networks favor lower-band spectrum for better coverage. Vehicle-to-vehicle (V2V) c ...
    Dataset Supporting Files
  • Rapid and Accurate Assessment of Road Damage by Integrating Data from Mobile Camera Systems (MCS) and Mobile LiDAR Systems (MLS) [supporting dataset]
    Chen, Qi
    ORCID ICON IMG
    2024-04-30 | JSON
    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 ( ...
    Dataset
  • Artificial Intelligence Copyright and the Doctrine of Fair Use
    Artificial Intelligence, Copyright, and the Doctrine of Fair Use
    White, Enid
    2024-04-11 | MP4
    Wyoming Department of Transportation Research Manager Enid White's presentation covers copyright issues related to artificial intelligence (AI). There are differing perspectives as well as many lawsuits underway in this area of copyright law. Generative AI companies and Large Language Models mine data from the internet to train AI. Authors, researc ...
    Supporting Files
  • An Overview of AI Assurance for Transportation
    An Overview of AI Assurance for Transportation
    United States. Department of Transportation. Highly Automated Systems Safety Center of Excellence
    2024-04-01 | PDF
    AI assurance refers to the techniques, activities, and processes used to evaluate and assure expected properties of AI components or AI-enabled systems throughout the lifecycle of these components or systems. The properties may relate to performance, safety, or security. Typical examples of AI assurance techniques are verification, validation, and ...
  • Targeted Warning Messages to Protect Moving and Stationary Maintenance Lane Closures
    Targeted Warning Messages to Protect Moving and Stationary Maintenance Lane Closures
    Soltani, Iman ;
    Gao, Dechen
    2024-03-31 | PDF
    This report details the development and evaluation of an innovative component in a traffic management system aimed at enhancing safety in work zones through targeted warning messages. The primary objective of the system is to improve the rates of driver compliance with work zone guidelines presented on signages and message boards, which our studies ...
  • RiskBased MultiThreat DecisionSupport Methodology for LongTerm Bridge Asset Management Volume 1 AIBased BridgeLevel Decision Support
    Risk-Based Multi-Threat Decision-Support Methodology for Long-Term Bridge Asset Management - Volume 1: AI-Based Bridge-Level Decision Support
    Ghavidel, Alireza ;
    Du, Ao
    2024-03-15 | PDF
    This project develops a methodology and tools for a risk-based multi-threat decision-support tool for long-term bridge asset management (BAM), with a particular focus on chronic aging-induced condition deterioration, and more abrupt and extreme seismic hazard impact. Specifically, a stochastic bridge condition deterioration and seismic damage simul ...
  • To Charge or Not to Charge: Enhancing Electric Vehicle Charging Management with LSTM-based Prediction of Non-Critical Charging Sessions and Renewable Energy Integration [supporting dataset]
    Tayarani, Hanif
    ORCID ICON IMG
    2024-03-13 | JSON
    This dataset provides detailed information on the destination labels for the trip trajectory and charging of 65 Battery Electric Vehicles in California in the eVMT dataset. This dataset includes the Tesla Model S and Chevrolet Bolt only. Additionally, the repository contains a Python script that trains a deep-learning model to predict the driving b ...
    Dataset
  • Assessment of Safe Work Indicators in Transportation Construction Using Personal Monitoring Systems
    Assessment of Safe Work Indicators in Transportation Construction Using Personal Monitoring Systems
    Clevenger, Caroline ;
    Abdallah, Moatassem
    2024-03-01 | PDF
    Construction projects require long hours where workers are subjected to intensive tasks such as hard manual labor, heavy lifting, and constrained working postures. Among the physiological metrics, heart rate (HR) is reported to be a good indicator of physical stress and workload. HR forecasting models have been used in various areas including cardi ...
  • Developing AIAssisted InSitu NDT Method for AirVoid Distribution Testing in Fresh and Hardened Concrete
    Developing AI-Assisted In-Situ NDT Method for Air-Void Distribution Testing in Fresh and Hardened Concrete
    Kong, Zhihao ;
    Mitra, Aritro Roy
    2024-03-01 | PDF
    Understanding the air void content in concrete is crucial since it significantly influences the durability and strength of the material, especially in environments susceptible to freeze-thaw cycles. This report introduces an advanced nondestructive testing (NDT) method for the in-situ detection of air voids in concrete by employing diffusive ultras ...
  • Prediction of Road Condition and Smoothness for Flexible and Rigid Pavements in Louisiana Using Neural Networks
    Prediction of Road Condition and Smoothness for Flexible and Rigid Pavements in Louisiana Using Neural Networks
    Wu, Zhong ;
    Liu, Yilong
    2024-03-01 | PDF
    The Louisiana Department of Transportation and Development (DOTD) currently utilizes pavement performance prediction models in treatment selection and budget planning. These models are solely based on the non-linear curve-fitting regression of existing pavement condition data available in its pavement management system (PMS) database. The objective ...
  • Prediction of Road Condition and Smoothness for Flexible and Rigid Pavements in Louisiana Using Neural Networks Technical Summary
    Prediction of Road Condition and Smoothness for Flexible and Rigid Pavements in Louisiana Using Neural Networks [Technical Summary]
    Wu, Zhong ;
    Zhang, Zhongjie "Doc"
    2024-03-01 | PDF
    The objective of this research was to develop both short- and long- term pavement performance and deterioration models that can be used to estimate future pavement conditions and smoothness using ANN modeling. Specifically, the short-term models were for the prediction of 2- and 4-year future pavement surface cracking percentages for the current Lo ...
  • Using Computer Vision Devices to Evaluate Bicycle and Pedestrian Improvements
    Using Computer Vision Devices to Evaluate Bicycle and Pedestrian Improvements
    Malarkey, Daniel ;
    Singh, Rubina
    2024-03-01 | PDF
    The design of urban streets and sidewalks must balance the mobility and safety requirements of pedestrians, cyclists, transit users, freight vehicles, and auto drivers. Modern engineers and designers supplement traditional traffic engineering approaches that focus on metrics for automobiles and trucks with more formal consideration of people travel ...
  • Securing Deep Learning Against Adversarial Attacks for Connected and Automated Vehicles
    Securing Deep Learning Against Adversarial Attacks for Connected and Automated Vehicles
    Pisu, Pierluigi ;
    Comert, Gurcan
    2024-03-01 | PDF
    Intelligent mobile robots, including autonomous agents, highly rely on the correctness of surrounding environment perception. Recently, Deep Learning-based perception models have been shown to be vulnerable to adversarial attacks through one kind of well-designed input called adversarial examples. Existing defenses include mainly adversarial traini ...
  • Quantification of Field Performance and Nondestructive Testing of Timber Bridges in Colorado Brief
    Quantification of Field Performance and Nondestructive Testing of Timber Bridges in Colorado [Brief]
    Kim, Yail Jimmy
    2024-03-01 | PDF
    This report presents two major aspects related to evaluating timber bridges with nondestructive testing: i) laboratory experiments and ii) field applications. The first part of the report discusses the degradation processes and resulting outcomes of structural timber, Douglas Fir, that is broadly used for bridge construction. In accordance with the ...
  • Artificial Intelligence Framework for Crosswalk Detection Across Massachusetts
    Artificial Intelligence Framework for Crosswalk Detection Across Massachusetts
    Apostolov, Atanas ;
    Xie, Yuanchang
    2024-02-01 | PDF
    The goal of this project was to develop an artificial intelligence (AI) framework to detect crosswalk locations across the state of Massachusetts, as well as their type classification (continental, parallel lines, or solid) and location category (intersection, midblock, or driveway). Aerial images downloaded from MassGIS were annotated, and these w ...
  • Community Augmented Rapidresponse to Events CARE Integrated Crisis Communication System
    Community Augmented Rapid-response to Events (CARE) Integrated Crisis Communication System
    Salley, Christin ;
    Xie, Jiajia
    2024-02-01 | PDF
    This project explores the potential of integrating social media data (i.e., Twitter/X) with data from community awareness applications (i.e., Waze) to bolster crisis communication and enhance the accuracy and promptness of incident identification, assessment, and reporting during emergencies. To navigate the challenges posed by varied data formats ...
  • Development of Railroad Trespassing Database Using Artificial Intelligence
    Development of Railroad Trespassing Database Using Artificial Intelligence
    Zaman, Asim ;
    Huang, Zhe
    2024-02-01 | PDF
    The Federal Railroad Administration (FRA) sponsored a research team from Rutgers University to develop a proof-of-concept Trespassing Database using Artificial Intelligence (AI) technology to automatically process large volumes of live or recorded video data. The team used the Rutgers AI algorithm to analyze over 27,000 hours of live video data and ...
  • Predictive RealTime Traffic Management in LargeScale Networks Using ModelBased Artificial Intelligence
    Predictive Real-Time Traffic Management in Large-Scale Networks Using Model-Based Artificial Intelligence
    Exploratory Advanced Research Program (U.S.)
    2024-02-01 | PDF
    This fact sheet highlights the research's team holistic framework to address the challenges in large-scale predictive traffic incident management (TIM). The research can be summarized as interconnecting subtask models that accomplish the following: Predict traffic speed. Detect traffic anomalies. Approximate traffic flow physics. Control traffic. E ...
261 - 280 / 613
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