Abstract
Eye tracking is increasingly employed to evaluate operators’ mental workload and the usability of interfaces. In this paper, eye tracking data were recorded for ten operators performing the simulated manually controlled rendezvous and docking (manual RVD) of two space vehicles. Indices such as blink rate, blink duration, percent eyelid closure (PERCLOS) were calculated to assess the mental workload and fatigue level of the operators. Fixation measures were analyzed to investigate the attention allocation of the operators on the different information areas on the display. Results showed that the workload of the RVD task was generally acceptable. However, workload increased in the accurate control stage (the last 20 meters’ approaching) compared to the tracking control stage (the more distant approaching). The fixation measures showed that human eyes were mostly fixed on the area of the spacecraft image, while numerical display areas provided compensatory information. The present study revealed that the design of the RVD interface supported human perception and task completion.
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Acknowledgements
This study is supported by National Key Research and Development Program (No. 2017YFB1300305), Foundation of Key Laboratory of Science and Technology for National Defense (No. 6142222030301, No. 614222204020617), Foundation of National Key Laboratory of Human Factors Engineering (No. SYFD170051802), and National Basic Research Program of China (No. 2011CB711000).
Compliance with Ethical Standards
The study was approved by the Logistics Department for Civilian Ethics Committee of China Astronaut Research and Training Center.
All subjects who participated in the experiment were provided with and signed an informed consent form.
All relevant ethical safeguards have been met with regard to subject protection.
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Tian, Y., Zhang, S., Wang, C., Yan, Q., Chen, S. (2019). Eye Tracking for Assessment of Mental Workload and Evaluation of RVD Interface. In: Long, S., Dhillon, B. (eds) Man-Machine-Environment System Engineering . MMESE 2018. Lecture Notes in Electrical Engineering, vol 527. Springer, Singapore. https://doi.org/10.1007/978-981-13-2481-9_2
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DOI: https://doi.org/10.1007/978-981-13-2481-9_2
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