Modelling for the assessment of pilot′s situational awareness in simulated spatial orientation based on eye tracking
10.3760/cma.j.cn11385420240315-00022
- VernacularTitle:基于眼动追踪的模拟空间定向飞行员情景意识评估建模
- Author:
Lu WANG
1
;
Qin YAO
1
;
Huibian ZHANG
1
;
Yawen WANG
1
;
Xianliang ZHAO
1
Author Information
1. 空军军医大学空军特色医学中心航空生理鉴定训练研究室，北京 100142
- Publication Type:Journal Article
- Keywords:
Cognition;
Visual perception;
Model;
Spatial disorientation;
Situation awareness;
Flight simulation
- From:
Chinese Journal of Aerospace Medicine
2024;35(3):161-167
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To propose a preliminary method for real-time assessment of pilot situational awareness based on assessing pilot′s visual gaze behavior during spatial orientation flight simulation.Methods:Fighter pilots who met the criteria were randomly selected by drawing lots. An eye-tracker was used to collect eye-track feature data from pilots in a flight simulator. The lightweight YOLOv8n model was used to detect the area of interest (AOI) in the training to construct the AOI gaze sequence feature data. The pilot′s illusory experiences and recovery from complex situations were recorded, and those were scored by the situation awareness global assessment technique to obtain such 3 situational awareness assessment levels as excellent, good, and fair which were used as labeled data. A transformer and inception module fusion situation awareness (Ti-SA) model was developed to extract and learn the features of eye-tracking time-series data and AOI gaze time-series data and was compared with other commonly used models in the field of multidimensional time-series classification.Results:Thirty fighter pilots were enrolled, all male, aged 23-38 years old, with flying hours of 300-2 200 h, were included in the study. Nineteen temporal features of pilots′ eye movement trajectories were obtained by eye-tracker. By situation awareness global assessment, 12 pilots were scored to excellent level, 15 to good level and 3 to fair level. When Ti-SA model was applied to the experimental dataset, the accuracy was 92.18%, the precision was 92.95%, the recall was 95.49%, and the F1 score was 94.20%, which were better than other commonly used models in the field of multidimensional time-series classification.Conclusions:The study indicates that the proposed dataset construction method and Ti-SA model can effectively assess the level of pilot situational awareness in spatial orientation flight simulation.
