AI Use Case LibraryDoD FM · Federal · Audit · Finance · OMB 2025
Home/Browse catalog/OMB Individually Reported/OMB-IND-DOT-1000031
OMB Individually Reported

Crash Parameter Prediction

Low riskExact public inventory row

Description

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. Delta-V and PDOF are two most important parameters affecting injury outcome. D

Detailed example

Delta-V & PDOF

AI / analytics pattern

Other

Automation level / stage

a) Pre-deployment – The use case is in a development or acquisition status.

Controls / human review

ATO: Yes; PIA: No

Source

OMB 2025 Federal Agency AI Use Case Inventory

Related

More from Transportation

OMB-IND-NASA-5OMB Individually Reported

Autoresolver/Tailored Arrival Manager

The Autoresolver system is a tool for autonomous air traffic management. It is designed to perform many of the tasks that air-traffic controllers have historically performed inclu…

OMB Individually ReportedTransportationLow risk
OMB-IND-NASA-11OMB Individually Reported

Explainable and robust deep semi-supervised model for multi-class anomaly detection in flight data

This model is a semi-supervised deep learning based anomaly detection for aircraft flight data. It is designed to work when a small subset of data is reviewed and labeled by exper…

OMB Individually ReportedTransportationLow risk
OMB-IND-NASA-18OMB Individually Reported

Machine Learning Airport Surface Model: Airport Configuration Prediction

The ML-airport-configuration software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models inte…

OMB Individually ReportedTransportationLow risk
OMB-IND-NASA-19OMB Individually Reported

Machine Learning Airport Surface Model: Arrival Runway Prediction

The ML-airport-arrival-runway software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models int…

OMB Individually ReportedTransportationLow risk
OMB-IND-NASA-20OMB Individually Reported

Machine Learning Airport Surface Model: Departure Runway Prediction

The ML-airport-departure-runway software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models i…

OMB Individually ReportedTransportationLow risk
OMB-IND-NASA-23OMB Individually Reported

Machine Learning Airport Surface Model: Taxi-out Prediction

The ML-airport-taxi-out software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended…

OMB Individually ReportedTransportationLow risk