Trusted and exPlainable Artificial Intelligence for Saving Lives (TruePAL) Technology for First Responder Safety

Overview

Development stage

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

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Fatalities caused by emergency vehicle collisions are 4.8 times higher for emergency responders than the national average. The Trusted and exPlainable Artificial Intelligence for Saving Lives (TruePAL) project was funded by DOT to study the AI technology for saving first responders and roadside crews lives in and around active traffic. The TruePAL, an AI assistant, provides real-time warning of risks by analyzing the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. A deep neural network (DNN) is developed to detect and track vehicles, pedestrians, traffics signs, etc., and a Non-Axiomatic Reasoning System (NARS) to analyze the risk and provide prioritized warning messages. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL AI assistant demonstrated real-time crash warning and human factor design capabilities using a CARLA simulator. The TruePAL project has developed cutting-edge AI tools: a Human-machine AI interface has potential to save lives for first responders and roadside crews.

Expected benefits

Fatalities caused by emergency vehicle collisions are 4.8 times higher for emergency responders than the national average. The Trusted and exPlainable Artificial Intelligence for Saving Lives (TruePAL) project was funded by DOT to study the AI technology for saving first responders and roadside crews lives in and around active traffic. The TruePAL, an AI assistant, provides real-time warning of risks by analyzing the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. A deep neural network (DNN) is developed to detect and track vehicles, pedestrians, traffics signs, etc., and a Non-Axiomatic Reasoning System (NARS) to analyze the risk and provide prioritized warning messages. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL AI assistant demonstrated real-time crash warning and human factor design capabilities using a CARLA simulator. The TruePAL project has developed cutting-edge AI tools: a Human-machine AI interface has potential to save lives for first responders and roadside crews.

System outputs

timely warning to drivers and roadside crews to avoid crashes

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported