Difference between revisions of "AI Safety Aviation"
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[[File:AVIAIDecomp.png | 600px | Decomposition of 3ADC]] | [[File:AVIAIDecomp.png | 600px | Decomposition of 3ADC]] | ||
[[File:AVIAIDSM.png | | [[File:AVIAIDSM.png | 400px | DSM of 3ADC]] | ||
= Roadmap OPD = | = Roadmap OPD = |
Revision as of 06:07, 5 November 2024
Roadmap Overview
Focuses on the integration of artificial intelligence, particularly machine learning, into safety-critical aviation systems while maintaining the highest standards of safety and trustworthiness. It encompasses a phased approach, starting with human assistance/augmentation (Level 1 AI), progressing to human-AI teaming (Level 2 AI), and ultimately advancing to more automated solutions (Level 3 AI). Key aspects include developing AI assurance frameworks, addressing human factors in AI integration, implementing safety risk mitigation strategies, and ensuring compliance with evolving regulatory requirements. This technology aims to enhance aviation safety, efficiency, and performance across various domains including aircraft design and operation, air traffic management, and unmanned aircraft systems.
Scope Down Idea (Draft)
- Hybrid cockpit with AI supporting pilot by improving situational awareness and translate pilot intent to automated systems.
DSM Allocation
Roadmap OPD
Figures of Merit
Figure of Merit | Description | Trends | Units |
---|---|---|---|
Incident Rate | Rate of incidents and accidents normalized by flight time aircraft | decreasing |
|
System Maintainability | How much time is spend maintaining aircraft systems, measured by comparing maintenance time per flight time | decreasing |
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Response Time | Time required to identify and mitigate safety issues | flat |
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System Uptime | Amount of time aircraft is available to be dispatched on a mission as a percentage of wall time | increasing |
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Cognitive Load on Crew | As measured by industry standard NASA TLX score | flat |
|