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A Study on the Effects of Fatigue Driving and Drunk Driving on Drivers’ Physical Characteristics

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Version 2 2015-02-25, 22:18
Version 1 2014-11-17, 00:00
journal contribution
posted on 2015-02-25, 22:18 authored by Xingjian Zhang, Xiaohua Zhao, Hongji Du, Jian Rong

Objective: The purpose of this study was to analyze the effects of fatigue driving and drunk driving on drivers’ physical characteristics; to analyze the differences in drivers’ physical characteristics affected by different kinds of fatigue; and to compare the differences in the effects of the 2 driving states, fatigue driving and drunk driving.

Methods: Twenty-five participants’ physical characteristics were collected under 5 controlled situations: normal, tired driving, drowsy driving, drowsiness + tired driving, and drunk driving. In this article, fatigue driving refers to tiredness and drowsiness and includes 3 situations: tired driving, drowsy driving, and drowsiness + tired driving. The drivers’ physical characteristics were measured in terms of 9 parameters: systolic blood pressure (SBP), heart rate (HR), eyesight, dynamic visual acuity (DVA), time for dark adaption (TDA), reaction time to sound (RTS), reaction time to light (RTL), deviation of depth perception (DDP), and time deviation of speed anticipation (TDSA). They were analyzed using analysis of variance (ANOVA) with repeated measures. Binary logistical regression analysis was used to explain the relationship between drivers’ physical characteristics and the two driving states.

Results: Most of the drivers’ physical characteristic parameters were found to be significantly different under the influence of different situations. Four indicators are significantly affected by fatigue driving during deep fatigue (in decreasing order of influence): HR, RTL, SBP and RTS. HR and RTL are significant in the logistical regression model of the drowsiness + tired driving situation and normal situations. Six indicators of the drivers’ physical characteristics are significantly affected by drunk driving (in decreasing order of influence): SBP, RTL, DDP, eyesight, RTS, and TDSA. SBP and DDP have a significant effect in the logistical regression model of the drunk driving situation and the normal situation.

Conclusions: Both fatigue driving and drunk driving are found to impair drivers’ physical characteristics. However, their impacts on the parameters SBP, HR, eyesight, and TDSA are different. A driver's physical characteristics will be impaired more seriously when he continues driving while drowsy, compared to driving under normal situation. These findings contribute to the current research on identifying drivers’ driving state and quantifying the effects of fatigue driving and drunk driving on driving ability and driving behavior.

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