Chenyuan Yang

The operation and support (OS) officer is responsible for buoyancy regulation and fault detection of onboard equipment in the civil submersible. The OS officer carries out the above tasks through the human-machine interface (HMI) of a submersible buoyancy regulation and support (SBRS) system. However, the OS officer often faces uneven task frequency produced by fault tasks, which leads to an unbalanced mental workload and individual failures. To address this issue, we proposed a human-machine function allocation method based on level of automation (LOA) taxonomy and submersible task complexity (STC), aimed at improving human-machine cooperation in submersible fault detection tasks. Based on this method, we identified the LOA2 as the optimal human-computer function allocation scheme. In this study, three measurement techniques (subjective scale, work performance, and physiological status) were used to test 15 subjects to validate the effectiveness of the proposed optimal human-machine function allocation scheme. The GAMM test results also indicate that the proposed optimal human-machine function allocation scheme (LOA2) can improve the work performance of the operating system officials under low or high workloads and reduce the subjective workload.

Workload (WL) measurement is a crucial foundation for human–machine collaboration, particularly in high-stress multitasking environments such as manned vehicle operations during emergencies, where operators often experience High Workload (HWL) levels, increasing the risk of human error. To address this challenge, this study introduces a novel WL measurement method that combines Task Demand Load (TDL) and Subject Load Capacity (SLC) to quantitatively assess operator workload. This method was validated through experiments with 45 subjects using the Environmental Control and Atmospheric Regeneration (ECAR) system. The statistical results showed that as the designed WL levels increased, the Average Workload (AWL), the NASA-TLX score, and the work time percentage increased significantly, while the task accuracy and the fixation duration decreased significantly. These results also revealed the impact of WL levels on human responses (such as subjective feeling, work performance, and eye movement). In addition, very strong correlations were found between AWL measurements and NASA-TLX scores (r = 0.75, p < 0.01), task accuracy (r = −0.73, p < 0.01), and work time percentage (r = 0.97, p < 0.01). Overall, these results proved the effectiveness of the proposed method for measuring WL. On this basis, this study defined WL thresholds by integrating task accuracy with AWL calculations, providing a framework for the dynamic management of task allocation between humans and machines to maintain operators within optimal WL ranges.

Individuals exposed to elevated noise levels experience heightened emotional intensity, leading to increased cognitive disruption and a higher likelihood of accidents. This study seeks to investigate the impact of noise exposure on human cognitive performance, and the moderating role of emotion. Twelve healthy male college-age students underwent exposure to three noise conditions, each characterized by different sound pressure levels and sharpness. Each condition included an initial acoustic/thermal adaption period lasting approximately 40 min, followed by intermittent questionnaire tests and a battery of computerized cognitive tests. Statistical analysis revealed that reducing noise levels proved advantageous, enhancing perceived sound quality, positive emotions, and auditory perception abilities, while concurrently reducing false alerts and accelerating execution speed. Many of these effects were found to be counteracted by elevated sharpness. Correlation analyses and partial least squares structural equation modeling (PLS-SEM) results suggested that human emotions mediate the relationship between noise exposure and cognitive performance. The potential underlying mechanism suggests that negative feelings towards noise contribute to poor emotional states, subsequently influencing cognitive processes and impairing executive function. The outcomes of this study provide valuable insights into the mechanism of noise exposure and its effects on human cognition and subjective perceptions.