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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 241 - 260 of 613 results
  • Convolutional Neural Network Learning Approaches for Driver Injury Severity Classification and Application in SingleVehicle Crashes in RITI Communities
    Convolutional Neural Network Learning Approaches for Driver Injury Severity Classification and Application in Single-Vehicle Crashes in RITI Communities
    Zhang, Guohui ;
    Yang, Hanyi
    2024-06-30 | PDF
    It is crucial to examine the characteristics and attributes of traffic crashes in Rural, Isolated, Tribal, or Indigenous (RITI) communities using statistical and data-driven methods. However, traditional crash data analysis faces challenges due to unobserved heterogeneities and temporal instability. To address these issues, a fusion convolutional n ...
  • Incorporating Use Inspired Design in Providing Safe Transportation Infrastructure for RITI Communities
    Incorporating Use Inspired Design in Providing Safe Transportation Infrastructure for RITI Communities
    Chen, Roger B. ;
    Harirchi, Poya
    2024-06-30 | PDF
    In this study, we focus on automating road marking extraction from the HDOT MLS point cloud database, managed by Mandli. Mandli is a company specializing in highway data collection, including LiDAR. Mandli has cooperated with various Department of Transportation throughout the United States. Here, we focus on infrastructure elements related to non- ...
  • Development of Pavement Performance Models for MDOT A Neural Network Approach
    Development of Pavement Performance Models for MDOT: A Neural Network Approach
    Yasarer, Hakan ;
    Najjar, Yacoub M.
    2024-06-26 | PDF
    The continuous investigation into the mechanical properties and rehabilitation management of existing pavements is vital for the sustainability and efficiency of transportation systems. The Mississippi Department of Transportation (MDOT) database, containing over 40 million records, necessitates modernized decision-making models that align with cur ...
  • Assessing Cyclists Stress on A LargeScale A Practical SmartphoneBased DataDriven Approach
    Assessing Cyclist's Stress on A Large-Scale: A Practical Smartphone-Based Data-Driven Approach
    Li, Ming ;
    Deb, Shuchi
    2024-06-23 | PDF
    Cycling presents a compelling solution for promoting personal health and environmental well-being, particularly for short-distance travel. Despite its numerous advantages, cycling uptake in the United States remains disproportionately low, primarily due to safety concerns. Traditional frameworks for assessing cyclist stress are hindered by their im ...
  • DeepLearningBased Radio Channel Prediction for VehicletoVehicle Communications
    Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications
    Molisch, Andreas F ;
    Chu, Lei
    2024-06-15 | PDF
    Reliable and efficient V2V communications are essential for driver-assistance systems to reduce accidents and improve energy efficiency through efficient convoying. A key challenge is that resource allocation for communication must rely on the current propagation channel state, but vehicles only have past measurements. Therefore, effective channel ...
  • MultiRobot Teaming for Inspection of Hydraulic Structures Final Report
    Multi-Robot Teaming for Inspection of Hydraulic Structures: Final Report
    Lattanzi, David ;
    Aminfar, Kiyarash
    2024-06-14 | PDF
    Inspecting hydraulic structures, including capturing deformations in the deck and detecting defects in the piers, presents numerous challenges. These structures require evaluation both above and below the water surface, and existing approaches do not support quantitative and integrated asset management practices. This study develops a multimodal co ...
  • Mobile PhoneBased Artificial Intelligence Development for Maintenance Asset Management Final Report
    Mobile Phone-Based Artificial Intelligence Development for Maintenance Asset Management [Final Report]
    Kuang, Biao ;
    Chen, Jianli
    2024-06-01 | PDF
    Transportation asset management requires timely information collection to inform relevant maintenance practices. Traditional data collection methods often necessitate manual operation or the use of specialized equipment, e.g., light detection and ranging (LiDAR), which can be labor-intensive and costly to implement. With advancements in computing t ...
  • Mobile PhoneBased Artificial Intelligence Development for Maintenance Asset Management Research Brief
    Mobile Phone-Based Artificial Intelligence Development for Maintenance Asset Management [Research Brief]
    Chen, Jianli ;
    Kuang, Biao
    2024-06-01 | PDF
    To achieve the research objectives of this project, four specific tasks are involved: Task 1: A comprehensive literature review is conducted to explore and examine existing technologies and practices related to transportation asset collection and inspection, including emerging AI technologies. Task 2: A mobile phone mounted on a vehicle is used to ...
  • To Charge or Not to Charge Enhancing Electric Vehicle Charging Management with LSTMbased Prediction of NonCritical Charging Sessions and Renewable Energy Integration
    To Charge or Not to Charge: Enhancing Electric Vehicle Charging Management with LSTM-based Prediction of Non-Critical Charging Sessions and Renewable Energy Integration
    Tayarani, Hanif ;
    Nitta, Christopher J
    2024-06-01 | PDF
    To maximize the greenhouse gas (GHG) emission reduction potential of Battery Electric Vehicles (BEVs), it is critical to develop EV dynamic charging management strategies. These strategies leverage the temporal variability in emissions associated with generated electricity to align EV charging with periods of low-carbon power generation. This study ...
  • Smart Robot Design and Implementation to Assist Pedestrian Road Crossing
    Smart Robot Design and Implementation to Assist Pedestrian Road Crossing
    Kulhandjian, Hovannes
    ORCID ICON IMG
    2024-06-01 | PDF
    This research focuses on designing and developing a smart robot to assist pedestrians with road crossings. Pedestrian safety is a major concern, as highlighted by the high annual rates of fatalities and injuries. In 2020, the United States recorded 6,516 pedestrian fatalities and approximately 55,000 injuries, with children under 16 being especiall ...
  • Utilizing Traffic Signal Pedestrian PushButton Data for Pedestrian Planning and Safety Analysis
    Utilizing Traffic Signal Pedestrian Push-Button Data for Pedestrian Planning and Safety Analysis
    Singleton, Patrick A. ;
    Rafe, Amir
    2024-06-01 | PDF
    Transportation planning, traffic monitoring, and traffic safety analysis require detailed information about pedestrian volumes, but such data are usually lacking. Fortunately, recent research has demonstrated the accuracy of pedestrian volumes estimated from push-button data contained within high-resolution traffic signal controller log data. Such ...
  • Smart Robot Design and Implementation to Assist Pedestrian Road Crossing Research Brief
    Smart Robot Design and Implementation to Assist Pedestrian Road Crossing [Research Brief]
    Kulhandjian, Hovannes
    ORCID ICON IMG
    2024-06-01 | PDF
    This research addresses a pressing issue: pedestrian safety, especially in school zones. With a high number of pedestrian fatalities and injuries reported annually, particularly among children, there is a critical need for innovative solutions to enhance safety at crossroads. Traditional methods, such as deploying school personnel to assist childre ...
  • Utilizing Traffic Signal Pedestrian PushButton Data for Pedestrian Planning and Safety Analysis Research Brief
    Utilizing Traffic Signal Pedestrian Push-Button Data for Pedestrian Planning and Safety Analysis [Research Brief]
    Singleton, Patrick A. ;
    Mekker, Michelle
    2024-06-01 | PDF
    This project takes advantage of novel pedestrian push-button traffic signal data to advance pedestrian traffic monitoring and improve pedestrian traffic safety. The data are applied as estimates of volume and exposure, often alongside advanced machine learning techniques.
  • DeepLearningBased Radio Channel Prediction for VehicletoVehicle Communications Project Summary
    Deep-Learning-Based Radio Channel Prediction for Vehicle-to-Vehicle Communications [Project Summary]
    Molisch, Andreas F
    ORCID ICON IMG
    2024-05-31 | PDF
    Driver-assistance systems are essential to reduce accidents and improve energy efficiency through efficient convoying. To improve their effectiveness, it is important that vehicles are able to communicate with each other, informing each other of their intentions, and warning each other of obstacles or cross traffic that only some of the vehicles mi ...
  • Modeling Dynamic Behavior of Navigable Inland Waterways
    Modeling Dynamic Behavior of Navigable Inland Waterways
    Nachtmann, Heather ;
    Bu, Fan
    2024-05-10 | PDF
    The inland waterway freight system is a valuable and underutilized asset within the United States (U.S.) transportation system, providing an economical and environmentally sound mode for moving cargo. Container on Barge (COB) transportation is an intermodal freight transport mode that moves shipping containers via barges on navigable inland and int ...
  • Dynamic Prediction of Shared Micromobility Usage with MultiTask Learning Brief
    Dynamic Prediction of Shared Micromobility Usage with Multi-Task Learning [Brief]
    Guo, Yujie ;
    Zhang, Yu
    2024-05-01 | 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 ...
  • Computer Vision for Traffic Monitoring
    Computer Vision for Traffic Monitoring
    Thompson, Matthew ;
    Lowry, Michael
    2024-05-01 | PDF
    This project examined computer vision applications for traffic monitoring and safety analysis. The focus was on evaluating the open-source computer vision code that we developed. Three case studies were completed using our computer vision code. The code was written in Python and uses a detection model called YOLOv8. The first case study demonstrate ...
  • Impervious Surfaces from High Resolution Aerial Imagery Cities in Fresno County
    Impervious Surfaces from High Resolution Aerial Imagery: Cities in Fresno County
    Ahn, Yushin ;
    Poythress, Richard
    2024-05-01 | PDF
    This study investigates impervious surfaces - areas covered by materials with restricted water permeability, such as pavement, sidewalks, and parking lots-due to their crucial role in influencing water dynamics within urban landscapes. The impermeability of these surfaces disrupts natural water absorption processes, resulting in adverse environment ...
  • Assessment of Contextual Complexity and Risk Using Unsupervised Clustering Approaches with Dynamic Traffic Condition Data Obtained from Autonomous Vehicles
    Assessment of Contextual Complexity and Risk Using Unsupervised Clustering Approaches with Dynamic Traffic Condition Data Obtained from Autonomous Vehicles
    Ogle, Jennifer H ;
    Bendigeri, Vijay
    2024-05-01 | PDF
    Traditional road safety assessment methodologies rely heavily on AADT (Annual Average Daily Traffic) data estimates to account for variability in traffic operations. Unfortunately, this approach does not consider the driving environment's fast-changing dynamics, which can influence contextual complexity and risk. This research report presents a met ...
  • A Statistical and Machine Learning Approach to Assess Contextual Complexity of the Driving Environment Using Autonomous Vehicle Data Technology Transfer Activities
    A Statistical and Machine Learning Approach to Assess Contextual Complexity of the Driving Environment Using Autonomous Vehicle Data- Technology Transfer Activities
    Ogle, Jennifer H ;
    Bendigeri, Vijay
    2024-05-01 | PDF
    Traditional road safety assessment methodologies rely heavily on AADT (Annual Average Daily Traffic) data estimates to account for variability in traffic operations. Unfortunately, this approach does not consider the driving environment's fast-changing dynamics, which can influence contextual complexity and risk. This research report presents a met ...
241 - 260 / 613
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