Analysis of Highway Driving Fatigue Patterns in Heavy Truck Drivers

doi:10.12141/j.issn.1000-565X.240411

Abstract

Abstract:

Long-distance heavy truck drivers are prone to fatigue when driving on highways, threatening road safety. To systematically investigate the fatigue characteristics and their progression of heavy truck drivers during prolonged highway driving, an on-road driving experiment was conducted for truck drivers operating continuously on highways. Cameras were mounted to continuously monitor the driver’s seat, with driving behaviors correlated to fatigue levels-such as the frequencies of rearview mirror-checking and non-driving-related movements-quantified through video analysis. An eye tracking device was utilized to acquire and process ocular metrics-including blink duration and pupil diameter-during driving sessions. Subsequent analysis employed function fitting, driving behavior characterization, and multilayer perceptron (MLP) modeling to examine the progression patterns of fatigue characteristics during prolonged highway driving, the correlation between fatigue manifestations and driving behaviors, and safety-critical time thresholds for continuous driving duration of truck drivers. The results indicate that the safe threshold for continuous driving time for truck drivers is between 3.6 and 3.7 hours. Regarding passive fatigue generated during driving tasks, detection of fatigue onset via mean blink duration occurred 5~15 minutes prior to drivers’ active fatigue countermeasures in 48.69% of observed instances. A notable reduction in passive fatigue frequency was observed during the 1.5~2.0 h interval of continuous driving. Statistical analysis revealed significant correlations between both rearview mirror-checking frequency and non-driving-related movements (NDRMs) with mean blink duration. An MLP model constructed using the frequencies of rearview mirror-checking, NDRM occurrences, and communication behaviors as predictors without ocular metrics achieved an 80.2% detection rate for passive fatigue during driving. These research outcomes provide theoretical foundations and practical references for developing video-based fatigue monitoring systems, implementing fatigue alerts, and enhancing driving safety for heavy trucks.

Key words: traffic safety, driving fatigue, multilayer perceptron, continuous driving, heavy trucks, driving task-related fatigue

CLC Number:

U411

LI Chen, CHEN Feng, DING Wenlong, PAN Xiaodong. Analysis of Highway Driving Fatigue Patterns in Heavy Truck Drivers[J]. Journal of South China University of Technology(Natural Science Edition), 2025, 53(10): 29-39.

Figures/Tables 15

Fig.1

Table 1

Overview of the main highway sections of the experimental approach"

高速公路路段	车道数量	货车限速/（ $k m ∙ h - 1$ ）
首都环线高速（太行山高速互通-固安东）	双向四车道	80
张石高速（宣大高速互通-荣乌高速互通）	双向四车道	80
荣乌高速（津同立交桥-张石高速互通）	双向四车道	80
京台高速（永清北-津雄高速互通）	双向八车道	100
津晋高速（塘沽收费站-当城互通）	双向六车道	100

Table 1

Table 2

Fig.2

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Fig.11

Table 3

Variable selection for model construction"

变量代号	变量含义
$m i$	时间窗 $i$ 中观察后视镜次数 $M i$ 与本次实验均值 $M ¯$ 的比值
$g i$	时间窗 $i$ 中小动作次数 $G i$ 与本次实验均值 $G ¯$ 的比值
$Δ m i$	时间窗 $i$ 中 $m i$ 与上一时间窗 $m i - 1$ 的差值
$Δ g i$	时间窗 $i$ 中 $g i$ 与上一时间窗 $g i - 1$ 的差值
$a i$	时间窗 $i$ 中使用对讲机的次数
$b i$	时间窗 $i$ 中使用蓝牙接打电话的次数
$c i$	时间窗 $i$ 中使用微信对讲的次数

Table 3

Fig.12

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