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Article type: Research Article
Authors: Li, Kai Waya; b | Peng, Luc; * | Zhao, Caijunb; d | Khaday, Samsiyab
Affiliations: [a] School of Mines, China University of Mining and Technology, Xuzhou, China | [b] Department of Industrial Management, Chung Hua University, Hsin-Chu, Taiwan | [c] College of Information Management, Nanjing Agricultural University, Nanjing, China | [d] School of Safety and Engineering Management, Hunan Institute of Technology, Hengyang, China
Correspondence: [*] Address for correspondence: Lu Peng, College of Information Management, Nanjing Agricultural University, Nanjing, China. E-mail: [email protected].
Abstract: BACKGROUND:Mental workload is one of the important variables in understanding human performance in drone operation. OBJECTIVE:To test the effects of gender, age group, flight route, and altitude on the flight performance and mental workload of the novice drone operators. METHODS:Ten male and ten female participants without prior drone operating experience joined. They were split into two age groups. After attending a training, the participants operated a drone to perform photo taking missions under flight route and altitude conditions. The weighted NASA Task Load Index (TLX), Modified Cooper-Harper (MCH) scale, heart rate, and interbeat interval were measured to assess the mental workload of the participants. Flight time to complete the mission was adopted to indicate flight performance. RESULTS:The effect of age group was significant (p < 0.05) on flight time, weighted TLX score, and MCH score. Flight route and altitude were not significant on the two subjective ratings and two cardiac measures. CONCLUSION:The flight performance of younger participants was significantly better than that of their older counterpart. The effects of both the flight route and altitude on the perceived mental workload of the drone operators were insignificant. Both the weighted NASA TLX and MCH scales were appropriate in measuring the mental workload of the novice drone operators.
Keywords: Drone, human machine interface, remote control, aerial photography, NASA TLX
DOI: 10.3233/WOR-211222
Journal: Work, vol. 75, no. 1, pp. 181-193, 2023
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