Analysis of Highway Driving Fatigue Patterns in Heavy Truck Drivers

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.