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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 321 - 340 of 613 results
  • A Diagnostic Machine Learning Model for Air Brake Systems in Commercial Vehicles
    A Diagnostic Machine Learning Model for Air Brake Systems in Commercial Vehicles
    Darbha, Swaroop ;
    Rajagopal, Kumbakonam
    2023-11-01 | PDF
    Safely introducing autonomy to trucks requires monitoring their brake systems continuously. Out-of-adjustment push rods and leakages in the air brake system are two major reasons for increased braking distances in trucks, resulting in safety violations. Air leakages can occur due to small cracks or loose/improperly fit couplings, which do not affec ...
  • Influence of Pavement Conditions on Commercial Motor Vehicle Crashes
    Influence of Pavement Conditions on Commercial Motor Vehicle Crashes
    Arhin, Stephen ;
    Manandhar, Babin
    2023-11-01 | PDF
    Commercial motor vehicle (CMV) safety is a major concern in the United States, including the District of Columbia (DC), where CMVs make up 15% of traffic. This research uses a comprehensive approach, combining statistical analysis and machine learning techniques, to investigate the impact of road pavement conditions on CMV accidents. The study inte ...
  • The Use of Artificial Intelligence in Pavement Engineering
    The Use of Artificial Intelligence in Pavement Engineering
    Mikels, Natalie ;
    Kassem, Emad
    2023-11-01 | PDF
    The performance of asphalt pavements decreases with time because of traffic loading and environmental conditions. Performance decay models are needed in pavement management systems to program pavement preservation and rehabilitation treatments to extend the service life and improve the performance of flexible pavements. Many factors affect pavement ...
  • Promoting CAV Deployment by Enhancing the Perception Phase of the Autonomous Driving Using Explainable AI
    Promoting CAV Deployment by Enhancing the Perception Phase of the Autonomous Driving Using Explainable AI
    Dong, Jiqian ;
    Chen, Sikai
    2023-11-01 | PDF
    User trust is pivotal to autonomous vehicle (AV) operations which are driven by artificial intelligence (AI). A promising way to build user trust is to use explainable artificial intelligence (XAI) which requires the AI system to provide the user with the underlying explanations for its decisions. Motivated by the need to enhance user trust and the ...
  • Influence of Pavement Conditions on Commercial Motor Vehicle Crashes Research Brief
    Influence of Pavement Conditions on Commercial Motor Vehicle Crashes [Research Brief]
    Arhin, Stephen ;
    Manandhar, Babin
    2023-11-01 | PDF
    The study examined traffic crash data obtained from the Traffic Accident Reporting and Analysis Systems Version 2.0 (TARAS2) database and pavement condition data maintained by the District Department of Transportation (DDOT) in the District of Columbia. CMV crash data was specifically collected for crashes occurring on designated CMV routes between ...
  • Exploring the Use of Artificial Intelligence to Leverage TxDOT Data for Enhanced Corridor Management and Operations Project Summary
    Exploring the Use of Artificial Intelligence to Leverage TxDOT Data for Enhanced Corridor Management and Operations [Project Summary]
    Juri, Natalia Ruiz ;
    Perrine, Ken
    2023-10-31 | PDF
    This project explored the use and value of AI and ML in transportation taking a multi-pronged approach that includes a literature review, a workshop, a survey, the development of three prototype ML models for four high-priority use cases, and the field testing of one of the prototyped models. Initial tasks were exploratory in nature and led to a be ...
  • Artificial Intelligence for Optimal Truck Platooning: Impact on Autonomous Freight Delivery [supporting dataset]
    Liu, Tong ;
    Meidani, Hadi
    2023-10-06 | JSON
    The advancements in autonomous- and connected-vehicle technologies bring drastic changes in freight delivery. Vehicle-to-vehicle and vehicle-to-infrastructure communication has become a reality with the help of autonomous and connected vehicles. One of the most notable changes is the formation of truck platoons. Despite the numerous benefits of tru ...
    Dataset
  • Bicycle and Pedestrian Safety Research Project
    Bicycle and Pedestrian Safety Research Project
    Jackson, Steve ;
    Raymond, Paula
    2023-10-01 | PDF
    Crash typing is the process of analyzing crash details to categorize crashes into similar groups, which can help identify hotspots, rising problems, and deploy the most effective countermeasures. This research analyzed crashes involving motor vehicles and bicycles or pedestrians in Idaho between 2012 and 2021. Using the PBCAT2 methodology, with sup ...
  • Exploring AIBased Video Segmentation and Saliency Computation To Optimize ImageryAcquisition From Moving Vehicles
    Exploring AI-Based Video Segmentation and Saliency Computation To Optimize Imagery-Acquisition From Moving Vehicles
    Silva, Claudio T ;
    Ozbay, Kaan
    2023-10-01 | PDF
    In this study, a new dataset and tool were generated describing and mapping street-level infrastructure. The presented dataset, StreetAware, is generated from more than 7 hours of synchronized data collected at urban intersections by specialized Reconfigurable Environmental Intelligence Platform (REIP) sensors developed by the Visualization and Dat ...
  • Enhancing Erosion Resistance of Rock Shoulder by Considering Hydrodynamics
    Enhancing Erosion Resistance of Rock Shoulder by Considering Hydrodynamics
    Song, Chung R. ;
    Wood, Richard L.
    2023-10-01 | PDF
    Highway shoulder rocks are exposed to continuous erosion force due to unexpected floodings caused by climate change. The evaluation methods of the erosion resistance of highway shoulder rocks are not currently well-developed. This study developed a new large-scale testing device, the University of Nebraska-Lincoln Erosion Testing Bed (UNLETB), whic ...
  • Effectively Implementing Machine Learning with Office of Materials Technology
    Effectively Implementing Machine Learning with Office of Materials Technology
    Zhang, Yunfeng ;
    Xu, Jianshu
    2023-10-01 | PDF
    Machine learning models provide significant value for planning and asset management purposes by maximizing the usefulness of past data collection for decision-making and policy development. Newer and more powerful machine learning models not available in previous applications and research in highway transportation fields are investigated to address ...
  • Effectively Implementing Machine Learning with Office of Materials Technology Research Summary
    Effectively Implementing Machine Learning with Office of Materials Technology [Research Summary]
    Zhang, Yunfeng
    2023-10-01 | PDF
    Machine learning models provide significant value for planning and asset management purposes by maximizing the usefulness of past data collection for decision-making and policy development. Newer and more powerful machine learning models not available in previous applications and research in highway transportation fields are investigated to address ...
  • Erosion Resistant Rock Shoulder
    Erosion Resistant Rock Shoulder
    Song, Chung R. ;
    Wood, Richard L.
    2023-10-01 | PDF
    Highway shoulder rocks are exposed to continuous erosion force due to unexpected floodings caused by climate change. The evaluation methods of the erosion resistance of highway shoulder rocks are not currently well-developed. This study developed a new large-scale testing device, the University of Nebraska-Lincoln Erosion Testing Bed (UNLETB), whic ...
  • A Machine LearningBased System for Predicting Peak Flowrates of Nebraska Streams
    A Machine Learning-Based System for Predicting Peak Flowrates of Nebraska Streams
    Roy, Tirthankar ;
    Pokharel, Sudan
    2023-10-01 | PDF
    Accurate, early flood warnings are invaluable for ensuring transportation safety so that flood-prone roads can be closed well before they become hazardous. A flood forecasting system typically uses both hydrologic and hydraulic models. The latter requires peak flow information to calculate flood attributes, such as depth, velocity, and inundated ar ...
  • Modeling Naturalistic Driving Environment with HighResolution Trajectory Data
    Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data
    Feng, Shuo ;
    Yan, Xintao
    2023-10-01 | PDF
    For simulation to be an effective tool for the development and testing of autonomous vehicles, the simulator must be able to produce realistic safety-critical scenarios with distribution-level accuracy. However, due to the high dimensionality of real-world driving environments and the rarity of long-tail safety-critical events, how to achieve stati ...
  • RealTime Risk Prediction at Signalized Intersection Using Graph Neural Network Webinar
    Real-Time Risk Prediction at Signalized Intersection Using Graph Neural Network [Webinar]
    Sarkar, Abhijit ;
    Sonth, Akash
    2023-10-01 | PDF
    Sarkar, A. & Sonth, A. (2023, October 24). Real Time Risk Prediction at Signalized Intersection Using Graph Neural Network. Webinar SafeD Virtual Webinar. Includes PDF of PowerPoint slides and link to YouTube video of webinar.
    Supporting Files
  • Social CarpoolingBased Road Congestion Mitigation A ThreeLevel Analysis
    Social Carpooling-Based Road Congestion Mitigation: A Three-Level Analysis
    Chen, Peng ;
    Nguyen, Thang
    2023-09-30 | PDF
    Different from Transportation Network Companies and shared-car providers, social carpooling is personalized incentives-based and smartphone-enabled peer-to-peer ridesharing. Social carpooling emerges as a community-based strategy to reduce car ownership and mitigate congestion. It facilitates the transition from solo driving to effective carpooling ...
  • Learning Active Inference MODELs of Perception and Control Application to Car Following Task
    Learning Active Inference MODELs of Perception and Control: Application to Car Following Task
    Garcia, Alfredo
    ORCID ICON IMG
    2023-09-20 | 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 ...
  • A Diagnostic Machine Learning Model for Air Brake Systems in Commercial Vehicles [supporting dataset]
    Darbha, Swaroop ;
    Rajagopal, Kumbakonam
    2023-09-12 | JSON
    Safely introducing autonomy to trucks requires monitoring their brake systems continuously. Out-of-adjustment push rods and leakages in the air brake system are two major reasons for increased braking distances in trucks, resulting in safety violations. Air leakages can occur due to small cracks or loose/improperly fit couplings, which do not affec ...
    Dataset
  • Random ForestBased Covariate Shift in Addressing NonStationarity of Railway Track Data
    Random Forest-Based Covariate Shift in Addressing Non-Stationarity of Railway Track Data
    Balogun, Ibrahim ;
    Attoh-Okine, Nii O
    2023-09-06 | PDF
    For years, track geometry vehicles have been deployed to capture rail defects. However, the limitation associated with the operation is the possibility of non-stationarity of the observed measurements due to external influence. The effect of non-stationarity may lead to the false representation of track conditions and thereby increases the likeliho ...
321 - 340 / 613
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