A Situational Awareness-Driven Human-Machine Interface Framework for Enhancing Operators’ Performance in Agricultural Robotic Teleoperation

Abstract

Despite the increasing adoption of automated/autonomous guided vehicles (AGVs) in precision agriculture, existing human-machine interfaces (HMIs) remain function-centric, frequently neglecting the cognitive and user experience (UX) needs of non-technical operators. Consequently, current dashboards suffer from limited usability, high cognitive load, and reduced system transparency, increasing the risk of operator error. To address this gap within agricultural teleoperation interface design, this study presents a theory-driven HMI framework that systematically translates Endsley’s Situational Awareness (SA) theory (Perception, Comprehension, Projection) and ISO 9241 ergonomic principles into a structured three-panel AGV teleoperation interface. Unlike conventional function-oriented dashboards, the proposed framework organises interface components according to operator cognitive requirements to support information perception, comprehension, and projection during remote operation. A theory-driven agricultural teleoperation HMI framework was developed by translating cognitive and ergonomic principles into practical interface organization strategies. To formatively evaluate this SA-driven design architecture, we conducted a user-perception study with non-expert digitally literate participants (N = 20), evaluating three iterative HMI prototypes. The comparative results indicate that the SA-aligned layout received higher user ratings in perceived decision-support capability (SA3), cognitive workload reduction, and overall usability compared with baseline designs during formative evaluation. The study provides preliminary methodological guidance for agricultural teleoperation HMI design, while recognizing that objective operational validation with target agricultural users remains necessary.