Exploring Functionalities for an Intelligent Pilot Advisory System in Normal Operation

This paper delves into the functionalities of an Intelligent Pilot Advisory System (IPAS) in normal aviation operations. Building upon the foundational work of “Intelligent Pilot Advisory System: The Journey From Ideation to an Early System Design of an AI-Based Decision Support System for Airline Flight Decks” by Jakob Würfel et al., which primarily focused on emergency scenarios, this study extends the IPAS’s application to non-emergency contexts. Utilizing a user-centered approach, a workshop involving pilots, data scientists, and Human-Artificial Intelligence Teaming (HAT) experts was conducted to brainstorm and evaluate functionalities for this system in regular flight operations. The methodology combined creative and analytical techniques, including the 6-3-5 ideation method, mind mapping and design studio method, leading to rapid prototyping and iterative feedback. During the workshop, several key functionalities for the IPAS were identified, such as the Mission Monitoring and Advisory Function (MMAF), which provides real-time updates on flight-related factors, as well as the integration of pre-flight briefing and operational guidance. Based on the workshops results an early prototype was developed, showcasing a timeline-based presentation of information and interactive user interface elements. This prototype serves as the basis for initial feedback evaluation and ongoing refinement. By integrating AI and leveraging the amount of aviation data, this intelligent advisor aims to improve situational awareness, decision-making, and operational efficiency in normal flight operations. In this context, this paper highlights the need for extended pilot testing and integration with existing cockpit systems, emphasizing the importance of human-AI teaming aspects, customization, data security, and the system’s impact on pilot skills, training and the environment.