A Model for Quantifying Pilot's Situation Perception Based on Attention Allocation

With the rapid development of Unmanned Aerial Vehicle (UAV) technology, the tasks that pilots need to accomplish in human-machine collaborative operations are more and more complex; the cognitive load is getting heavier and the situation awareness status is seriously affected. In order to assess the pilot's situation awareness status, it is necessary to quantify its first level, known as situation perception. Therefore, in this paper, the SEEV attention allocation algorithm is improved based on the background of human-machine collaboration and a new model for quantifying pilot's situation perception is established based on attention allocation. The eye movement data of subjects is also collected through specific flight simulation experiments and the situation perception of the subjects is quantified in this paper. The final experimental results show that the main information that consumes most of the subjects' attention is the roll and attack angle information, the route map information and the aircraft attitude information which is much easier to be perceived by the subjects. The results are in compliance with the flight experimental settings and can provide data support to assess the pilot's situation awareness status in the future work.