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. 2013 Dec;19(4):287-300.
doi: 10.1037/a0034386. Epub 2013 Sep 16.

Active and passive fatigue in simulated driving: discriminating styles of workload regulation and their safety impacts

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Free PMC article

Active and passive fatigue in simulated driving: discriminating styles of workload regulation and their safety impacts

Dyani J Saxby et al. J Exp Psychol Appl. 2013 Dec.
Free PMC article

Abstract

Despite the known dangers of driver fatigue, it is a difficult construct to study empirically. Different forms of task-induced fatigue may differ in their effects on driver performance and safety. Desmond and Hancock (2001) defined active and passive fatigue states that reflect different styles of workload regulation. In 2 driving simulator studies we investigated the multidimensional subjective states and safety outcomes associated with active and passive fatigue. Wind gusts were used to induce active fatigue, and full vehicle automation to induce passive fatigue. Drive duration was independently manipulated to track the development of fatigue states over time. Participants were undergraduate students. Study 1 (N = 108) focused on subjective response and associated cognitive stress processes, while Study 2 (N = 168) tested fatigue effects on vehicle control and alertness. In both studies the 2 fatigue manipulations produced different patterns of subjective response reflecting different styles of workload regulation, appraisal, and coping. Active fatigue was associated with distress, overload, and heightened coping efforts, whereas passive fatigue corresponded to large-magnitude declines in task engagement, cognitive underload, and reduced challenge appraisal. Study 2 showed that only passive fatigue reduced alertness, operationalized as speed of braking and steering responses to an emergency event. Passive fatigue also increased crash probability, but did not affect a measure of vehicle control. Findings support theories that see fatigue as an outcome of strategies for managing workload. The distinction between active and passive fatigue is important for assessment of fatigue and for evaluating automated driving systems which may induce dangerous levels of passive fatigue.

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Figures

Figure 1
Figure 1
Workload (upper panel), task engagement (middle panel), and challenge appraisal (lower panel) by duration and fatigue condition (Study 1). Error bars in all figures are standard errors.
Figure 2
Figure 2
Standardized change scores for subjective state factors by fatigue condition (Study 1).
Figure 3
Figure 3
Appraisal and coping scales by condition (Study 1). (Uncontrol. = Uncontrollability)
Figure 4
Figure 4
Uncontrollability and emotion-focus coping over time (Study 1).
Figure 5
Figure 5
Standardized change scores for subjective state factors by fatigue condition (Study 2).
Figure 6
Figure 6
Task engagement by duration and fatigue condition (Study 2).
Figure 7
Figure 7
Appraisal and coping scales by fatigue condition (Study 2). (Uncontrol. = Uncontrollability)
Figure 8
Figure 8
Precritical event SDLP for five 30 s intervals, by fatigue condition (Study 2).
Figure 9
Figure 9
Response times for braking and steering by fatigue condition (Study 2).
Figure 10
Figure 10
Number of participants able to avoid collision by fatigue condition and duration (Study 2).

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