ASSESSMENT OF SITUATION AWARENESS FOR SEAFARERS USING EYE-TRACKING DATA

被引:0
|
作者
Virdi, S. S. [1 ]
Ng, Yong Thiang [2 ]
Liu, Yisi [2 ]
Tan, Kelvin [2 ]
Zhang, Daniel [2 ]
机构
[1] SMA Singapore Polytech, Singapore, Singapore
[2] CEMS Singapore Polytech, Singapore, Singapore
关键词
Situation Awareness; Competence Assessment; Human Factors Study; Eye Tracking; Navigation Simulator; COLLISIONS; LESSONS;
D O I
暂无
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Situation Awareness (SA) is the perception of the current situation, comprehension of its meaning, and projection of what is going to happen in the near future. It is crucial for navigators to possess high SA in a navigational Bridge to mitigate the risk of human errors and to improve navigational safety. However, the current methodology to assess SA mainly rely on human experts, which might bring in potential problems such as bias, work overload, and it is also hard for the human experts to capture every fine detail of the behaviour of the seafarers being assessed. To overcome these, an objective and automated way to assess Situation Awareness is needed. In this work, eye-tracking data is used for the assessment of SA. With the eye tracking device, it is possible to localize where the navigator is looking at, and by applying computer vision with deep learning algorithm, the ongoing activity being executed by the navigator could be identified. In total 7 activities (using RADAR, ECDIS, checking of ship's heading, and speed, checking data on Echo Sounder, and data related to ships maneuvering, and others) can be recognized which are used as indicators of SA. A set of training data was recorded using Tobii Pro Glasses 3 to train the deep learning algorithm and test the classification accuracy. To further verify the proposed eye-tracking based assessment, a preliminary experiment has been designed and carried out. Five subjects were recruited for data collection. A full-mission Advanced Navigation Research Simulator (ANRS) was used to provide scenarios for both training data collection and preliminary experiment. From the initial results, it shows that a recognition accuracy of >99% can be achieved, which gives positive support to the eye-tracking based recognition. The analytics results using data from preliminary experiment also show great potential in using eye-tracking to assess SA of navigators. The proposed assessment could be used in both simulator and on-board and for multiple purposes such as performance evaluation, promotion to the next rank, and Continuing Professional Development.
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页数:7
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