Update on Machine-Learned Correctness Properties

23AERP08_08

08/01/2023

Abstract
Content

A novel method which has the potential for improving the U.S. Navy's ability to perform continuous assurance on autonomous and other cyberphysical systems.

Naval Postgraduate School, Monterey, CA

Autonomous systems are poised to provide transformative benefits to society. Autonomous vehicles (AVs) have the potential to reduce the frequency and severity of collisions, enhance mobility for blind, disabled, and underage drivers, lower energy consumption and environmentally harmful emissions, and reduce population density in metropolitan regions. In civilian aviation, increasingly autonomous systems could mitigate two of the most costly features of human pilots: the cost associated with training and paying highly skilled operators, and the reduced efficiency incurred by flight time limitations and crew rest requirements.

Additionally, autonomous air traffic management systems could reduce the cognitive burden on air traffic controllers by automating the monitoring and analysis of high volumes of data, alerting a human operator only when complex decisions must be made to mitigate risk. Within the power distribution industry, innovations in “micro-grid” technology can allow better utilization of alternate energy sources while decreasing vulnerability to failure compared to current centralized power distribution, but such decentralization necessitates highly adaptive autonomous systems to carefully synchronize energy production and consumption. Medical devices are currently designed to function for a large group of patients with similar conditions, but adaptive patient-specific algorithms could respond more effectively to individual patient needs, increasing lifespan and quality of life.

Meta TagsDetails
Pages
2
Citation
"Update on Machine-Learned Correctness Properties," Mobility Engineering, August 1, 2023.
Additional Details
Publisher
Published
Aug 1, 2023
Product Code
23AERP08_08
Content Type
Magazine Article
Language
English