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

Dyani Saxby · Gerald Matthews · Joel S. Warm · Edward M. Hitchcock · Catherine E. Neubauer

218 citations0/0 files storedJournal of Experimental Psychology Applied

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Human-Automation Interaction and Safety Traffic and Road Safety Sleep and Work-Related Fatigue

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.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 218 citations exist upstream.

References

1988Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research 1990Multidimensional assessment of coping: A critical evaluation.1997Compensatory control in the regulation of human performance under stress and high workload: A cognitive-energetical framework 2010New perspectives in attentional control theory 2010The link between fatigue and safety 2003Monotony of road environment and driver fatigue: a simulator study 2002Fundamental dimensions of subjective state in performance settings: Task engagement, distress, and worry.2000Human Performance: Cognition, Stress and Individual Differences

Cited by

2016Age differences in the takeover of vehicle control and engagement in non-driving-related activities in simulated driving with conditional automation 2018Driver Vigilance in Automated Vehicles: Hazard Detection Failures Are a Matter of Time 2016How the Duration of Automated Driving Influences Take-Over Performance and Gaze Behavior 2020Multimodal Features for Detection of Driver Stress and Fatigue: Review 2022

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.