ABSTRACT
Road traffic accidents (RTA) can cause a large number of casualties and property losses. Driving fatigue is one of the important factors leading to RTA. Electrophysiological signals, as a kind of information feedback for the nervous system to regulate body functions, can reflect drivers’ fatigue state. However, there is a lack of systematic reviews on the current research on electrophysiological signals as information input of machine learning methods for driving fatigue recognition. By investigating fatigue-related literature, the current paper summarized the neural regulation mechanism of fatigue, clarified that driving fatigue is caused by both psychological and physiological loads, recognized inducing factors related to driving fatigue, and summed up electrophysiological signals now in use of driving fatigue recognition, as well as their physiological mechanisms and related indicators. Machine learning algorithms are widely used in identifying driving fatigue. Based on existing studies that used electrophysiological signals as information input source and applied various machine learning algorithms to build driving fatigue identification models, this paper compared the effectiveness of various machine learning algorithms, and described the advantages and disadvantages of supervised machine learning. It is pointed out that suitable classification algorithms should be selected according to sample conditions and model eigenvalues when applied to driving fatigue recognition. In addition, a variety of electrophysiological signals as information sources can help improve the accuracy of a fatigue recognition model, but the increase of model input eigenvalues cannot. Finally, the research progress of identification methods based on electrophysiological signals provided new opportunities for identifying driving fatigue.
ABSTRACT
The purpose of this study is to compare the road conditions (straight road, winding road and hill road) with the hand grip pressure force and muscle fatigue for male and female drivers. Ten subjects were participated in this study. The force measurement and electromyography (EMG) responses were taken and evaluated by using the tactile grip and pressure measurement (Grip System) and Electromyography (EMG) device. The result indicated that the winding road produced more muscle fatigue and high hand grip pressure force compared than downhill road, hill up road, and straight road for both male and female subjects. The result compared the muscle fatigue and hand grip pressure force between the first 15 minutes and last 15 minutes of driving activity. The muscle fatigue increasingly high for the last 15 minutes compared to first 15 minutes. However, the hand grip pressure forces become high during the winding road for first 15 minutes of driving session. The muscle fatigue become high as the hand grip pressure force value is high. Furthermore, the male drivers exert higher hand grip pressure force and higher muscle fatigue compared to female drivers. This study can be used as a guideline for the future studies, primarily in solving the driving fatigue problem among the Malaysian’s drivers. The method of this study could also be used for early detection of driver fatigue issues. Indirectly, the findings could reduce the number of car accidents in Malaysia.
ABSTRACT
Objective To investigate effects of driving fatigue on working memory. Methods The control group included 12 taxi drivers after adequate rest while the fatigue group included 27 taxi drivers who had been driving for 10h. Digit memory span, words span, Digit Subtraction Test, Random Number Generation test were used. Results Compared with the control(6.60 ±0.40,90.67 ±6.65,158.27 ±29.12,0.30 ±0.06,24.29 ±10.59,35.90 ± 10.64 ), driving fatigue group were significantly( P ＜ 0.05 )different in the number of backward number memory span( 5.37 ± 0.72 ), percentage of number of right reaction of the number of total reaction of Digit Subtraction Test(79.95 ± 8.04), total number of RNG( 88.33 ± 19.48 ), RNG(0.40 ± 0.05 ), Coupon( 12.35 ±12.88), NSQ(49.72 ± 8.06). Conclusion Driving fatigue can decline the working memory.
ABSTRACT
Objective To investigate effects of driving fatigue on auditory involuntary attention.Method Between-groups design was used.The control group included 13 taxi drivers after adequate rest while the fatigue group included 13 taxi drivers who had been driving for 10 h.Auditory oddball pattern was adopted.The standard stimulus was 800 Hz,probability 80%;target stimulus was 1 000 Hz,probability 10%;novel stimulus was sound generated by computer or other sound,probability 10%.Subjects were asked to press the mouse upon hearing the target sound.Result The distribution of P3a was mainly around the frontal-central area of the subjects in control group;the amplitude of P3a was evidently lowered in subjects after driving fatigue.Conclusion The ability of auditory involuntary attention declines after driving fatigue.