JASC Code classification in Safety Difficulty Reports (SDR)
AVS identified a need to derive the joint aircraft system codes (JASC) chapter codes from the narrative description within service difficulty reports (SDR), a form of safety event…
Offshore Precipitation Capability (OPC)
The AI/ML tool helps detect and predict where precipitation currently is and where it will be at the future at various altitudes in parts of the NAS that do not have traditional g…
Course Deviation Identification for Multiple Airport Route Separation (MARS)
The Multiple Airport Route Separation (MARS) program is developing a safety case for reduced separation standards between Performance Based Navigation (PBN) routes in terminal air…
Improve and Speed up the Certification Service Oversight Process Using Intelligent Document Review
Before digitization: * The Certification Services Oversight Process (CSOP) is a manually intensive paper process * Requires the public and small businesses to provide input for…
Determining Surface Winds with Machine Learning Software
Successfully demonstrated use of an AI capability to analyze camera images of a wind sock to produce highly accurate surface wind speed and direction information in remote areas t…
Remote Oceanic Meteorological Information Operations (ROMIO)
ROMIO is an operational demonstration to evaluate the feasibility to uplink convective weather information to aircraft operating over the ocean and remote regions. Capability conv…
Head Kinematics Prediction
Description: Utilize deep learning models for predicting head kinematics directly from crash videos. The utilization of deep learning techniques enables the extraction of 3D kinem…
Crash Parameter Prediction
Description: Utilize deep learning for predicting crash parameters, Delta-V (change in velocity) and PDOF (principal direction of force), directly from real-world crash images. De…
Crushed Aggregate Gradation Evaluation System
Description: Deep learning computer vision algorithms aimed at analyzing aggregate particle size grading. Input: Images of ballast cross sections
Automatic Track Change Detection Demonstration and Analysis
Description: DeepCNet-based neural network to identify and classify track-related features (e.g., track components, such as fasteners and ties) for ""change detection"" applicati…
Predictive Analytics Using Autonomous Track Geometry Measurement System (ATGMS) Data
Description: Leveraging large volumes of these recursive track geometry measurements to develop and implement automated machine-learning-based processes for analyzing, predicting,…
Integration of small Unmanned Aircraft System (sUAS) Geospacial Information System (GIS) Technologie
This use case will be used to enable new methods and tools that support the maintenance of life cycle of National Airpsace System (NAS) infrastructure.
Geolocating and Identifying Vehicle Hard Brake, Acceleration and Seat Belt Usage with CV Data
Description: The ongoing work leverages AI/ML in big traffic data analytics to identify roadway geolocations where potential safety issue may exist through the integration of con…
Path to Advanced Novel Data Analytics (PANDA), a data science lab.
Description: A data science lab established at Turner-Fairbank Highway Research Center.
Exploratory Advanced Research group of projects
Description: The Exploratory Advanced Research (EAR) Program addresses the need for longer term, higher risk research with the potential for transformative improvements to transpo…
Enterprise Knowledge Graph and Advanced AI Data Structures Collaboration Group
DOT-Private Sector collaboration to develop advanced AI data structure expertise, lessons learned, and best practices to accelerate AI development across the agency.
Transportation Use Case Knowledge Repository (TrUCKR)
TrUCKR is the CAIO managed DOT platform for tracking the Department's unclassified AI use case development, maturity, assessments, clearances, risk evaluations and mitigations, an…
NETT Council AI Coordination and Activities (AICA) Working Group
The AICA Working Group consists of Operating Administration (OA) and Secretarial Offices AI leaders and subject matter experts across the Department. It is chaired by the CAIO an…
DOT Workforce Acquisitions and Training Team
The Workforce Acquisitions and Training Team members are DOT OA and Secretarial Office leaders responsible for AI talent acquisition and training and inspiring the workforce to ac…
NETT Council Safety, Rights, and Security Review (SR2) Committee
The SR2 Committee reviews and approves the operational deployment of all AI use cases and the public sharing of use case data, models, and code. The SR2 Committee is also responsi…
DOT AI Procurement Team
The Procurement Team members are DOT OA and Secretarial Office leaders responsible for AI procurement and acquisitions.
DOT AI Emerging Technology Team
The AI Emerging Technology Team members are DOT OA and Secretarial Office leaders most knowledgeable in leading-edge AI technology, capacity, and capabilities.
NHTSA Interim Generative AI (GenAI) Usage Guidance
Guidelines on usage of commercially available Generative Artificial Intelligence (GenAI) Tools and Services.
DOT Generative AI (GenAI) Policy
Provide DOT-wide generative AI (GenAI) policy.