Green towing departure represents a significant approach towards achieving green civil aviation, offering greater efficiency and environmental benefits compared to traditional departure methods. To accurately predict pilots’ visual attention allocation during towing departure and ensure safe operations, this paper proposes a predictive model based on information expectancy and an enhanced information value function. To validate the model, an instrument monitoring experiment was conducted with 14 participants under varying task weights and information presentation formats in a towing-departure context. Gaze-point distribution was recorded as an indicator of attention allocation. Participants monitor target information displayed on a simulated Head-Up Display (HUD) interface and respond to anomalies by pressing designated keys. The experimental results indicate that there is a significant correlation and good agreement between the theoretical values of attention allocation calculated using the proposed model and the actual gaze point distributions observed in the experiment. These findings provide a basis for the design of aircraft cockpit display interfaces.

With the advantages of low fuel consumption, high departure efficiency, and green environmental protection, the new civil aircraft departure mode of towing taxi-out has become the preferred mode of civil aircraft departure for future smart airports. The process of civil aircraft towing departure requires close collaboration and effective communication among multiple staff members, and accidents are mostly caused by human errors. Therefore, it is crucial to perform human reliability analysis. However, there are few reports or human reliability studies on civil aircraft towing departure accidents. Although the Success Likelihood Index Method (SLIM) based on expert ex-perience may be an effective tool for assessing human reliability, SLIM relies heavily on expert judgment to determine model parameters, which makes the method subjective and uncertain to varying degrees. To overcome this, the present study uses the Demp-ster–Shafer evidence theory to extend SLIM by fusing the judgments given by different experts, providing more accurate and reliable results. Herein, the proposed model is used to study human reliability in the process of civil aircraft towing departure. The results are conducive to reducing the human error probability of the staff involved in the civil aircraft towing departure process and improving the overall safety level of departure operations.