HARVIS: a digital assistant based on cognitive computing for non-stabilized approaches in Single Pilot Operations

Abstract

With Single Pilot Operations, the work that was shared between crew members in the past will be assumed by one pilot. To maintain an adequate level of safety and support the single pilots’ performance and decision-making in complex situations, we investigated a concept of cognitive computing algorithms and adaptive automation implemented in a digital assistant. The aim of the present work was to assess if an Artificial Intelligence (AI) assistant could support pilots’ decision-making during a Non-Stabilized Approach (NSA). Method: A NSA assistant prototype based on pilots expertise and eye-tracking data was developed. We performed a human in the loop session with 7 professional pilots on ENAC A320 simulator and analyzed the impact of the assistant on operations, human performance and the safety feeling of pilots. Results: Generally, the assistant was appreciated and trusted by pilots. The system improved pilots’ decision-making in order to perform a go-around. Aspects like trust, complacency, usability and pilots’ physiological data monitoring were dominant discussion points. Discussion and conclusion: There were no evidence that the assistant reduced pilots’ workload, but it helped pilots focusing a bit more on the ‘wider picture’ since part of the monitoring task could be delegated to the assistant. Understanding the reason of a go-around alert appeared to be a key point for pilots to build trust.