Integrating Ergonomics Into Safety Management: A Conceptual Risk Assessment Model for Tower Controllers at Multiple Altitudes

Abstract

Plateau and high plateau airports aggravate tower controllers' vulnerability, facing high safety risks, yet the risk evaluation paradigm to manage safety at multiple altitudes still lacks. The study aimed to investigate the effects of altitudes on controllers' mental workload and fatigue to assess the safety risk and introduced voices, mental workload, and fatigue, into a conceptual risk assessment model. Controllers from the Civil Aviation Administration of China (CAAC) conducted the experimental tasks, reporting mental workload and perception fatigue across three altitudes: 0 m, 2243 m, and 3569.7 m. With experimental data: this research (1) quantitatively compared the voice feature differences with feature engineering, and an image quality measure, (2) explored the effects of altitude, sleep, and fatigue, (3) tested the effects of altitude and task complexity on mental workload, and (4) evaluated the airport safety risks under ergonomic factors. Notably, the study revealed that Log-Mel spectrograms outperformed Mel Frequency Cepstral Coefficients (MFCC) in severe fatigue detection. Altitude and task complexity had significant main effects on the mental workload, but altitude had no significant moderator effects on the relationship between sleep and fatigue. The simulation results show that under the low task complexity, the operation risk is low over three airport elevations (with the human error rate < 10 −3 ), whereas under the high task complexity, the operation risk increased with altitudes (from 1.73× 10 −3 to 1.02 × 10 −1 ). Together, these results suggest that ergonomic factors influenced airport safety risk at multiple altitudes and promising real-time fatigue detection with voice features at different altitudes.

Functional networks for ergonomics and reliability tasks on the 90th anniversary of A. Gubinsky and V. Evgrafov

“…The approaches to solving the problem proposed in (Bridges et al, 2010) one can see in Figure 5. Unfortunately, despite the increasing number of research devoted to the human-operator reliability (Asgari et al, 2017, Liaw et al, 2017, Shao et al, 2021, the problem of the ergonomic reserves identification to ensure the automated systems quality has not been fully resolved. The problem is associated with the need for a unified model of the human-operator activity that considers all its features and factors affecting it.…”