Task scene associated unmanned aerial vehicle pilot visual attention distribution mode extraction method

Abstract

The invention discloses a task scenario associated unmanned aerial vehicle pilot visual attention distribution mode extraction method, which comprises the steps of obtaining pilot attention distribution data through an eye tracker, dividing different task scenarios through flight parameter data, extracting pilot physiological signals to divide fatigue levels of the pilot physiological signals, anddistinguishing pilot attention distribution situations under different task scenes and different fatigue levels. An eye tracker collects eye movement data when a pilot executes a task under the simulation platform; performs segmentation clustering on the flight parameter high-dimensional time sequence, and dividing different task scenes; collects pilot electrocardiogram data for time-frequency domain analysis, and establishes a fatigue state discrimination classifier in combination with eye movement data and auditory response; attention distribution characteristics are represented through thepercentage of fixation points in the region of interest, the number of times of review and the importance degree, the attention distribution situation with the highest support degree is extracted toserve as a mode, the guidance effect can be achieved on control over pilots of the unmanned aerial vehicle, and the important significance is also achieved on optimization of interface setting of an unmanned aerial vehicle control platform.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicle flight control training, and specifically relates to a method for extracting the visual attention distribution mode of the drone pilot associated with the task scene, which can extract the visual attention distribution mode of the drone pilot associated with the task scene , and then used to guide the pilot's eye movement behavior. Background technique [0002] In the modern drone control system, the degree of automation is very high, and the main function of the drone pilot has changed from control to surveillance. When performing different flight tasks, UAV pilots need to monitor a variety of information at the same time, so there is an optimal visual attention distribution mode that enables pilots to complete information collection in the most accurate and timely manner. It has strong guiding significance for UAV pilots. In addition, this mode can also be applied to the ergonomics evalu...

AI Technical Summary

Problems solved by technology

However, the eye movement mode in this invention is only aimed at different frequency grating stimulation tasks, and is not suitable for relatively complex task situations such as UAV reconnaissance tasks.

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