Pilots' mental workload prediction based on timeline analysis.

Area of Science:

• Human-Computer Interaction
• Cognitive Engineering
• Aerospace Human Factors

Background:

• Aircraft cockpit design is critical for flight safety due to intensive human-computer interaction.
• Optimizing display interfaces in complex flight tasks is essential for mitigating pilot cognitive load.

Purpose of the Study:

• To propose a dynamic conceptual framework and timeline task analysis method for predicting mental workload.
• To quantify the dynamic time effect of mental workload and task type influences within a prediction model.

Main Methods:

• Developed a dynamic mental workload prediction model integrating attention resource allocation.
• Conducted ergonomics simulation experiments with performance, subjective (NASA-TLX), and eye-tracking data.

Main Results:

• The prediction model demonstrated high accuracy and effectiveness across various interfaces and tasks.
• Real-time monitoring of pilot mental workload state was successfully achieved.

Conclusions:

• The developed prediction model and experimental methods can optimize display interfaces and flight tasks.
• This approach helps prevent pilot overload throughout all flight phases, enhancing overall safety.