Abstract
Aiming to address the problems of high cognitive load and low information perception efficiency of complex information system interfaces in manned/unmanned cooperative operations, this study proposes an interface optimization method based on the intuitive interaction paradigm. By constructing a three-dimensional information architecture containing state parameters of multiple target types, UAV behavioural intent parameters, and target situational parameters, we designed an intergroup control experiment between traditional and intuitive interfaces.The experiment adopted a simulated battlefield mission paradigm, and synchronously recorded operators' behavioural performances (response time, correctness rate), oculomotor characteristics (fixations hotspots, scanning paths), and electroencephalographic signals (P300 amplitude and latency) and combined with a multimodal data fusion analysis method to verify the interface optimisation effect. The results showed that the intuitive interface performed better in terms of situational awareness, operational efficiency and task effectiveness, and the NASA-TLX cognitive load scores were lower than those of the traditional interface, with a significant difference between groups (p = 0.003).This study explored potential methods for the design of interfaces for complex information systems based on our experimental findings: (1) Suggesting that encoding multi-target state parameters with dynamic highlighting may improve multi-target tracking accuracy, particularly when a single-information carrier embeds ≤ 3 intuitive elements; (2) UAV intent parameters need to be designed differently based on semantic features, and flicker cues combined with colour stereotype encoding are adopted for preconditioned parameters, which can shorten the time of intent recognition; (3) Target situation parameters need to establish a local-global dynamic mapping mechanism, and iconized presentation can reduce the fixations dwell time compared to textual description.The findings from this study may offer preliminary insights and a potential theoretical foundation for future interface design of human-machine cooperative systems in dynamic high-stakes environments.