2002/09/01 by Mark S. Young, Neville A. Stanton · 398 citations
Engineering · Neuroscience · Psychology · #Applied psychology #Automation #Cognitive psychology #Computer science #Driving simulator #Engineering #Human-Automation Interaction and Safety #Human–computer interaction #Neural and Behavioral Psychology Studies #Psychology #Simulation #Sleep and Work-Related Fatigue #Task (project management) #Workload
paper · open access · doi:10.1518/0018720024497709
published in Human Factors The Journal of the Human Factors and Ergonomics Society 44(3), 365-375 (SAGE Publishing)
openalex publication_date 2002/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/26
This paper proposes a new theory to account for the effects of underload on performance. Malleable attentional resources theory posits that attentional capacity can change size in response to changes in task demands. As such, the performance decrements associated with mental underload can be explained by a lack of appropriate attentional resources. These proposals were explored in a driving simulator experiment. Vehicle automation was manipulated at 4 levels, and mental workload was assessed with a secondary task. Eye movements were also recorded to determine whether attentional capacity varied with mental workload. The results showed a clear decrease in mental workload associated with some levels of automation. Most striking, though, were the results derived from the eye movement recordings, which demonstrated that attentional capacity varies directly with level of mental workload. These data fully supported the predictions of the new theory. Malleable attentional resources theory suggests that future vehicle designers should employ their technology in driver support systems rather than in automation to replace the driver. The implications of this theory are discussed with regard to capacity models of attention as well as to the design of future vehicle systems.