The low-pressure (and low-oxygen) environment in plateau regions affects drivers’ psychophysiological states and, thus, driving behavior and road safety. Six scenarios of expressway exit ramps were constructed based on the UC/win-road simulator to quantitatively analyze the effect of the plateau environment on workload state. A total of 50 participants in Nanjing (altitude 50 m) and 50 participants in Lhasa (altitude 3,650 m) were recruited for the simulation experiments. Based on the principal component analysis, a sample entropy index (SEI) was constructed to reflect the drivers’ psychophysiological levels by combining the sample entropy of electroencephalogram (EEG) signals β%, β/(α+θ), β/α, and heart rate (HR). Meanwhile, the pupil area change rate and the percentage of fixation time and duration within the region of interest were analyzed to characterize the drivers’ visual workload. Based on the psychophysiological and visual load, the differences in workload states among plain and plateau drivers were analyzed using a regression model and a one-way analysis of variance (ANOVA) test. At the same time, the changing trends of the drivers’ workload states in the curved section of the exit ramp under different scenarios were analyzed. The plateau drivers experienced a higher level of mental stress and greater psychological load. Furthermore, the higher radius of horizontal curves reduced the visual load level for drivers when traveling on the highway exit ramp sections. These findings should serve as a valuable reference for refining the design of plateau expressway exit ramps and providing a theoretical basis for improving driving safety in plateau areas.


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    Title :

    Analysis of Drivers’ Workload States on Highways in High Elevation Regions


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2024-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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