Development of a Rotorcraft Human-Machine Interface for Automatic Takeoff and Landing Systems on Unprepared Areas

Abstract

Helicopter missions experience various critical safety and efficiency challenges during landing and takeoff on unprepared areas. To address these, automatic takeoff and landing functions are being developed, such as the Airbus ENGEL system. This paper presents the design and evaluation of an interactive 3D exocentric head-down display for supervising the ENGEL system. Due to the dynamic risks of operations on unprepared areas, the human-machine interface includes predictive path preview modalities and proximal tethered orbit perspectives to maintain 360-degree spatial awareness. Using a desktop-based prototype, an exploratory usage-driven analysis is conducted across nominal and non-nominal scenarios for a cohort consisting of one experimental test pilot and three aviation experts (𝑁 = 4). The study aims to understand usage-behavior, perceived workload and situation awareness, and the system’s contribution to effective decision-making for mission efficiency. Results suggest a strong use of predictive modes during low-critical phases to assess anomalies found in high-risk phases such
as landing. Furthermore, despite an increase in workload ratings during non-nominal obstacle events, mission understanding was not compromised. This indicates a successful conversion of physical effort into effective cognitive support. Consequently, the implementation supports timely decision-making, ensuring early planning and optimizing mission efficiency. Future research recommends evaluating a cockpit-integrated system to further validate these findings under a realistic operational context.