Autonomous driving paper index
Evaluation of the sensitivity ocular and performance indicators for driver fatigue assessment in a driving simulator
One-line summary
Fatigue is a significant risk factor contributing to accidents in the transportation sector, particularly in bus operations.
Engineering notes
Twenty-four-hour sleep deprivation was associated with significantly increased levels of fatigue.
Chinese explanation / 中文解读
中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Fatigue is a significant risk factor contributing to accidents in the transportation sector, particularly in bus operations. Signs of fatigue can be identified using fatigue detection technologies. However, there is still ongoing debate regarding which parameter is most effective for detecting fatigue. This study aimed to identify the most sensitive parameters for fatigue detection. A total of 15 participants were included in this within-subject study, in which each participant completed both a baseline condition and a fatigue condition involving 24 h of wakefulness. The results of the study revealed that the percent miss of the Sustained Attention Test (SAT) is a parameter that effectively predicts fatigue. Additionally, the mean Psychomotor Vigilance Test (PVT) and minor lapses PVT demonstrated excellent accuracy in detecting fatigue. Twenty-four-hour sleep deprivation was associated with significantly increased levels of fatigue.
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