Adaptive Cockpit

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.

Roadmap Model

Figures of Merit

Important FOMs for 3AISC

Figure of Merit	Description	Trends	Units
Incident Rate	Rate of incidents and accidents normalized by flight time aircraft		$\frac{\text{incidents}}{\text{passenger mile}}$
System Maintainability	How easy it is to maintain the aircraft systems, measured by comparing maintenance time per flight time		$\frac{\text{maintenance hours}}{\text{passenger mile}}$
System Ease of Operation	Measure how easy it is to operate the aircraft by comparing number of personnel required to operate a vehicle per flight hour		$\frac{\text{\# of personnel}}{\text{passenger mile}}$
Response Time	Time required to identify and mitigate safety issues		$\text{minutes}$
System Uptime	Amount of time aircraft is available to be dispatched on a mission as a percentage of wall time		$\text{\%}$
Cognitive Load on Crew	As measured by industry standard NASA TLX score		$\text{unitless}$