Cognitive Response of Underground Car Driver Observed by Brain EEG Signals

In auxiliary transportation within mines, accurately assessing the cognitive and response states of drivers is vital for ensuring safety and operational efficiency. This study investigates the effects of various vehicle interaction stimuli on the electroencephalography (EEG) signals of mine transport vehicle drivers, analyzing the cognitive and response states of drivers under different conditions to evaluate their impact on safety performance. Through experimental design, we simulate multiple scenarios encountered in real operations, including interactions with dynamic and static vehicles, personnel, and warning signs. EEG technology records brain signals during these scenarios, and data analysis reveals changes in the cognitive states and responses of drivers to different stimuli. The results indicate significant variations in EEG signals with interactions involving dynamic and static vehicles, personnel, and warning signs, reflecting shifts in the cognitive and response states of drivers. Additionally, the study examines the overall impact of different interaction objects and environments. The detailed analysis of EEG signals in different scenarios sheds light on changes in perception, attention, and responses related to drivers, which is critical for advancing safety and sustainability in mining operations.

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Publication Details

Journal
Sensors
Published
2024-12-04
DOI
https://doi.org/10.3390/s24237763
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.64
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article

Cognitive Response of Underground Car Driver Observed by Brain EEG Signals

Yunwang Li, Yizhe Zhang, Lunfeng Guo, Bing Miao et al.
1 citations
Sensors
Human-Automation Interaction and Safety
0.64
article

Cognitive Response of Underground Car Driver Observed by Brain EEG Signals

Yunwang Li, Yizhe Zhang, Lunfeng Guo, Bing Miao, Xiusong You
article en
1 citations

Abstract

In auxiliary transportation within mines, accurately assessing the cognitive and response states of drivers is vital for ensuring safety and operational efficiency. This study investigates the effects of various vehicle interaction stimuli on the electroencephalography (EEG) signals of mine transport vehicle drivers, analyzing the cognitive and response states of drivers under different conditions to evaluate their impact on safety performance. Through experimental design, we simulate multiple scenarios encountered in real operations, including interactions with dynamic and static vehicles, personnel, and warning signs. EEG technology records brain signals during these scenarios, and data analysis reveals changes in the cognitive states and responses of drivers to different stimuli. The results indicate significant variations in EEG signals with interactions involving dynamic and static vehicles, personnel, and warning signs, reflecting shifts in the cognitive and response states of drivers. Additionally, the study examines the overall impact of different interaction objects and environments. The detailed analysis of EEG signals in different scenarios sheds light on changes in perception, attention, and responses related to drivers, which is critical for advancing safety and sustainability in mining operations.

SensorsVol. 24(23)
China University of Mining and Technology (CN), China Academy of Safety Sciences and Technology (CN), Ministry of Transport (CN)
Openalex Percentile: Top 25%
Human-Automation Interaction and Safety
0.64
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