A Study on the Error Occurrence and Human Information Processing Time Influenced by the Fluctuation of Working Memory Resource Capacity

Karashima, Mitsuhiko; Saito, Murako

doi:10.1207/s15327566ijce0502_1

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…More recently, Wickens, Xu, Helleberg, and Marsh (2001) suggested effort conservation as the explanation for why pilots in a simulated aviation task actually devoted more visual attention to an instrument panel when the task was easier. Finally, the concept of fluctuating resource pools has been aired by Karashima and Saito (2001), in their proposed fluctuation of working memory hypothesis. Although these authors presented a very detailed explanation of how capacity fluctuates, they failed to offer any reasoning as to why it does so (see also Young & Stanton, 2002, for a discussion of working memory vs. attentional resource models).…”

Section: Malleable Attentional Resources Theorymentioning

confidence: 99%

Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance

Young¹,

2002

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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 four 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 malleable attentional resources theory. The implications of this theory are discussed with regard to capacity models of attention, as well as to the design of future vehicle systems.

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Section: Malleable Attentional Resources Theorymentioning

confidence: 99%

Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance

Young¹,

2002

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Gaps in the Control of Automated Vehicles on Roads

Calvert

Arem

Hagenzieker

et al. 2021

IEEE Intell. Transport. Syst. Mag.

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Increased on-road testing and market availability of partially automated vehicles (AV) offers researchers and developers the opportunity to evaluate the AV's performance. The occurrence of new types of accidents involving AV's has sparked questions in regard to who is actually in control over and responsible for AV control. In this contribution, we suggest a potential discrepancy in AV control with the review of recently documented accidents involving AV's. The identification of a gap in control is performed using a recently formulated moral philosophical framework of Meaningful Human Control (MHC). This shows a discrepancy between the attribution of responsibility and the ability of a human to fulfil the role assigned to them. While a gap in control is not evident from the viewpoint of operational control, it requires the more intricate concept of MHC to expose it. Recommendations are further made that AV developers and vehicle approval authorities should consider control from a MHC perspective to avoid future gaps in control with the resulting consequences.

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Re-conceptualization of Human-Centered System : Learning Processes in Viable and Purposeful Action and Multimodal Methodology

むら子

2003

J. SOFT

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A Study on the Error Occurrence and Human Information Processing Time Influenced by the Fluctuation of Working Memory Resource Capacity

Cited by 3 publications

References 22 publications

Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance

Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance

Gaps in the Control of Automated Vehicles on Roads

Re-conceptualization of Human-Centered System : Learning Processes in Viable and Purposeful Action and Multimodal Methodology

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