Method for constructing a cluster unmanned aerial vehicle operation duration determination model based on mental fatigue

Huapeng Liu; Xiaochuan Zhao; Leiming Jin; Yunduo Feng; Bingxu Wang; Ying Liu; Tiange Hong

doi:10.1117/12.3040287

4 September 2024 Method for constructing a cluster unmanned aerial vehicle operation duration determination model based on mental fatigue

Huapeng Liu, Xiaochuan Zhao, Leiming Jin, Yunduo Feng, Bingxu Wang, Ying Liu, Tiange Hong

Author Affiliations +

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132591X (2024) https://doi.org/10.1117/12.3040287
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

This article designs a cognitive data collection paradigm that integrates PVT (Psychomotor Vigilance Task) with cluster missions to activate operator mental fatigue states and accurately collect sample data. Based on the sample data, a support vector machine (SVM) based classification model for the mental fatigue states of cluster drone operators is trained and constructed. Using this model, a cluster drone operation duration determination model is developed by setting criteria for extreme fatigue states and calibrating model thresholds. Through 100 rounds of 5-fold cross-validation on the dataset, the results indicate an accuracy rate of 95.5% for determining the mental fatigue states of cluster drones.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huapeng Liu, Xiaochuan Zhao, Leiming Jin, Yunduo Feng, Bingxu Wang, Ying Liu, and Tiange Hong "Method for constructing a cluster unmanned aerial vehicle operation duration determination model based on mental fatigue", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132591X (4 September 2024); https://doi.org/10.1117/12.3040287

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