Fatigue and Secondary Media Impacts in the Automated Vehicle: A Multidimensional State Perspective

Author:

Neubauer Catherine E.1,Matthews Gerald2,De Los Santos Erika P.2ORCID

Affiliation:

1. Army Research Laboratory, Human Research and Engineering Directorate, US Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD 21005, USA

2. Department of Psychology, George Mason University, 4400 University Dr, Fairfax, VA 22030, USA

Abstract

Safety researchers increasingly recognize the impacts of task-induced fatigue on vehicle driving behavior. The current study (N = 180) explored the use of a multidimensional fatigue measure, the Driver Fatigue Questionnaire (DFQ), to test the impacts of vehicle automation, secondary media use, and driver personality on fatigue states and performance in a driving simulator. Secondary media included a trivia game and a cellphone conversation. Simulated driving induced large-magnitude fatigue states in participants, including tiredness, confusion, coping through self-comforting, and muscular symptoms. Consistent with previous laboratory and field studies, dispositional fatigue proneness predicted increases in state fatigue during the drive, especially tiredness, irrespective of automation level and secondary media. Similar to previous studies, automation slowed braking response to the emergency event following takeover but did not affect fatigue. Secondary media use relieved subjective fatigue and improved lateral control but did not affect emergency braking. Confusion was, surprisingly, associated with faster braking, and tiredness was associated with impaired control of lateral position of the vehicle. These associations were not moderated by the experimental factors. Overall, data support the use of multidimensional assessments of both fatigue symptoms and information-processing components for evaluating safety impacts of interventions for fatigue.

Publisher

MDPI AG

Subject

Public Health, Environmental and Occupational Health,Safety Research,Safety, Risk, Reliability and Quality

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