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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 381 - 400 of 613 results
  • Machine LearningBased HighFidelity Mesoscopic Modeling Tool for Traffic Network Optimization
    Machine Learning-Based High-Fidelity Mesoscopic Modeling Tool for Traffic Network Optimization
    Heckendorn, Robert B ;
    Eapen, Neeta A
    2023-06-01 | PDF
    Traffic signal control of the future will adapt in real time to traffic, driving, and environmental conditions. The adaptations will require real-time optimization based on traffic monitoring. However, for optimization to work, it must be able to predict what traffic will do in response to changes in signal timing. Furthermore, it must do this pred ...
  • Using Machine Learning Models to Forecast Electric Vehicle Destination and Charging Event
    Using Machine Learning Models to Forecast Electric Vehicle Destination and Charging Event
    Tayarani, Hanif ;
    Nitta, Christopher J
    2023-06-01 | PDF
    California's regulations on greenhouse gas emissions have led to increased adoption of Battery Electric Vehicles (BEVs) in the state. However, range anxiety remains a challenge for BEV drivers. To address this issue, accurately predicting BEV charging behavior and informing drivers when they need to charge is crucial. This study aims to develop a p ...
  • Exploring Costeffective Computer Vision Solutions for Smart Transportation Systems
    Exploring Cost-effective Computer Vision Solutions for Smart Transportation Systems
    Gao, Jingqin ;
    Xu, Chuan
    2023-05-01 | PDF
    The key accomplishments of the project are summarized as follows. The team conducted a literature review on computer vision for smart cities with a focus on transportation and summarized a resource list that lists publicly available traffic camera systems in the U.S. The team also established an automatic pipeline for data acquisition and developed ...
  • Exploring Costeffective Computer Vision Solutions for Smart Transportation Systems Literature Review
    Exploring Cost-effective Computer Vision Solutions for Smart Transportation Systems [Literature Review]
    Gao, Jingqin ;
    Ozbay, Kaan
    2023-05-01 | PDF
    Computer vision is reshaping the transportation industry and bringing its unique capabilities to the table to enable next generation smart transportation systems in many different ways. The state-of-the-art of IoT strategies and computer vision techniques is well-studied in the literature, some has already been tested and used for certain use cases ...
  • Preconstruction Support Cost Hours Estimating on Caltrans Pavement Rehabilitation Projects
    Preconstruction Support Cost Hours Estimating on Caltrans Pavement Rehabilitation Projects
    Blampied, Nigel ;
    Shehab, Tariq
    2023-05-01 | PDF
    Because the construction phase accounts for the majority of project costs for pavement rehabilitation projects, most research on infrastructure project cost estimating focuses on that phase, rather than on the preconstruction phases. Nevertheless, costs incurred prior to construction, referred to in this report as "preconstruction costs" are signif ...
  • Towards the Implementation of a Geotechnical Asset Management Program in the State of Georgia
    Towards the Implementation of a Geotechnical Asset Management Program in the State of Georgia
    Macedo, Jorge ;
    Burns, Susan E.
    2023-05-01 | PDF
    Experiences at U.S. departments of transportation (DOTs) have demonstrated the value of geotechnical asset management (GAM) to enable a framework for informed decisions that align the DOT's objectives with investment and performance targets. However, because Georgia currently lacks a such a program, this study was performed to set the stage for dev ...
  • Preconstruction Support Cost Hours Estimating on Caltrans Pavement Rehabilitation Projects Research Brief
    Preconstruction Support Cost Hours Estimating on Caltrans Pavement Rehabilitation Projects [Research Brief]
    Blampied, Nigel ;
    Shehab, Tariq
    2023-05-01 | PDF
    The California Department of Transportation (Caltrans) budgets approximately $600 million per year for preconstruction work on the State Highway Operation and Protection Program. In the 2020-2021 Fiscal Year, $169 million of this money was spent on preconstruction work on pavement rehabilitation projects. Caltrans and the California Transportation ...
  • RealTime DataBased Decision Support System for Arterial Traffic Management
    Real-Time Data-Based Decision Support System for Arterial Traffic Management
    Hadi, Mohammed ;
    Elefteriadou, Lily
    2023-04-20 | PDF
    This study developed and evaluated a TRPS strategy based on supervised and unsupervised machine learning combined with signal timing optimization to address the issues with traditional TRPS. The strategy fills an important gap in providing a proactive traffic control that makes use of Automated Traffic Signal Performance Measures (ATSPM) measures-b ...
  • Deep Reinforcement Learning for Multiasset Infrastructure Management Incorporating Traffic Operations Adaptations and Control
    Deep Reinforcement Learning for Multi-asset Infrastructure Management Incorporating Traffic Operations Adaptations and Control
    Papakonstantinou, K G ;
    Stoffels, S. M.
    2023-04-01 | PDF
    Preserving structural integrity through inspections and maintenance (I&M) is a critical and recurrent task that involves complex decisions strategically placed in both space and time to ensure the longevity and reliability of infrastructure assets. At the regional scale, the optimal management of entire networks amplifies the complexity of these de ...
  • Automated Safety Assessment of Rural Roadways Using Computer Vision
    Automated Safety Assessment of Rural Roadways Using Computer Vision
    Mashhadi, Ali Hassandokht ;
    Rashidi, Abbas
    2023-04-01 | PDF
    Roadside elements play an important role in the number and severity of crashes. Rigid obstacles (trees, rocks, embankments, etc.), guardrails, clear zones, and side slopes are among the factors that might affect roadside safety. The Federal Highway Administration (FHWA) presented a rating system to help DOTs and transportation agencies make better ...
  • Automated Track Change Detection Technology for Enhanced Railroad Safety Assessment
    Automated Track Change Detection Technology for Enhanced Railroad Safety Assessment
    Harrington, Ryan ;
    de Oliveira Lima, Arthur
    2023-04-01 | PDF
    The Rail Transportation and Engineering Center at the University of Illinois at Urbana-Champaign and Railmetrics, Inc. evaluated the use of 3D laser scanning, Deep Convolutional Neural Networks (DCNNs), and change detection technology for railway track safety inspections. Researchers evaluated the potential use of these combined technologies to pro ...
  • Evaluating the Effectiveness of Computer Vision Systems Mounted on Shared Electric Kick Scooters to Reduce Sidewalk Riding
    Evaluating the Effectiveness of Computer Vision Systems Mounted on Shared Electric Kick Scooters to Reduce Sidewalk Riding
    Oshanreh, Mohammad Mehdi ;
    MacKenzie, Donald
    2023-04-01 | PDF
    The objective of this study was to assess the impact of feedback and speed limitations on the riding behavior of e-scooter riders on sidewalks. To do this, we used data provided by Spin, a US-based micromobility company, on Santa Monica e-scooters that were equipped with an AI camera to monitor surface type. We conducted an experiment in which 50 e ...
  • Study of Impacts of Technology on the Future Workforce at the MDOT SHA
    Study of Impacts of Technology on the Future Workforce at the MDOT SHA
    Han, Chaodong ;
    Otto, James
    2023-04-01 | PDF
    Artificial intelligence, robotic process automation, natural language processing and virtual collaboration technologies are transforming the landscape of the office and administrative workforce by automating non-value added, repetitive tasks and processes, as well as supporting remote and flexible work. The scope of this study is to provide recomme ...
  • RoadSide Based Cybersecurity in Connected and Automated Vehicle Systems
    Road-Side Based Cybersecurity in Connected and Automated Vehicle Systems
    Masoud, Neda ;
    Wang, Yiyang
    2023-04-01 | PDF
    In this study, we develop a comprehensive framework to model the impact of cyberattacks on safety, security, and head-to-tail stability of connected and automated vehicular platoons. First, we propose a general platoon dynamics model with heterogeneous time delays that may originate from the communication channel and/or vehicle onboard sensors. Bas ...
  • Multisource Data Fusion for RealTime and Accurate Traffic Incident Detection via Predictive Analytics
    Multisource Data Fusion for Real-Time and Accurate Traffic Incident Detection via Predictive Analytics
    Stamatiadis, Polichronis ;
    Gartner, Nathan H.
    2023-04-01 | PDF
    The objectives of this study are to (1) identify data sets available to MassDOT that can be used for real-time incident detection; (2) investigate how data from different sources can be integrated to improve incident detection; and (3) develop guidance for establishing trigger points to alert Highway Operations Center (HOC) operators about incident ...
  • Deep Learning for Unmonitored Water Level Prediction and Risk Assessment 2023
    Deep Learning for Unmonitored Water Level Prediction and Risk Assessment [2023]
    Corns, Steven M ;
    Long, Suzanna K
    2023-03-30 | PDF
    In this research, deep learning models for the prediction of river gauge heights were developed using publicly available data for the 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-performan ...
  • An Active Inference Model of Car Following Advantages and Applications
    An Active Inference Model of Car Following: Advantages and Applications
    Wei, Ran ;
    McDonald, Anthony D
    2023-03-28 | PDF
    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 ...
  • Automated Lane Change and Robust Safety
    Automated Lane Change and Robust Safety
    Jiang, Zhong-Ping ;
    Ozbay, Kaan
    2023-03-01 | PDF
    Firstly, to guarantee stability and robustness in the face of parametric uncertainties, non-linearities, and modeling errors, we have proposed a data-driven optimal control algorithm to solve the lane-changing problem of AVs which is inspired by reinforcement learning and adaptive dynamic programming. Secondly, we have developed a lane change decis ...
  • AttentionBased Data Analytic Models for Traffic Flow Predictions
    Attention-Based Data Analytic Models for Traffic Flow Predictions
    Kumar, Kaushal ;
    Wei, Yupeng
    2023-03-01 | PDF
    Traffic congestion causes Americans lose millions of hours and dollars each year. In fact, 1.9 billion gallons of fuel are wasted each year due to traffic congestion, and each hour stuck in traffic costs about $21 in wasted time and fuel. The traffic congestion can be caused by various factors, such as bottlenecks, traffic incidents, bad weather, w ...
  • AttentionBased Data Analytic Models for Traffic Flow Predictions Brief
    Attention-Based Data Analytic Models for Traffic Flow Predictions [Brief]
    Kumar, Kaushal ;
    Wei, Yupeng
    2023-03-01 | PDF
    Traffic congestion makes Americans waste millions of hours and dollars each year. In this work, the authors analyze traffic flow data from the Caltrans Performance Measurement System (PeMS) and use deep learning algorithms to predict traffic flow accurately.
381 - 400 / 613
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