Attention, automaticity, and automation : New perspectives on mental underload and performance
Attention, automaticity, and automation : New perspectives on mental underload and performance
Commentators on vehicle technology predict that in 100 years, cars will be fully automated, and the traditional concept of a driver will be redundant. Some vehicle devices that represent a first step towards this goal are already on the market, and others are due to follow in the near future. Whilst vehicle automation is not unfamiliar on today's roads, new technologies such as ACC and AS have the potential to reduce driver mental workload in addition to relieving physical workload. Previous research suggests, though, that reducing mental workload is not necessarily a good thing. It is widely believed that mental underload can be detrimental to performance. Despite the wealth of literature establishing a relation between underload and performance decrements, there are very few attempts to explain why this may be the case. The present thesis reviews theories of attention and skill development, as well as the literature on mental workload and automation, to synthesise a new explanation for the effect of mental underload on performance. A theory of malleable attentional resources is proposed to account for the effects of underload, and consideration is given to how the development of automaticity may influence performance in underload situations. It is hypothesised that attentional capacity can shrink in response to reduced task demands, and that performance in such underload situations is dependent on the level of operator skill.
Four experiments were conducted in the Southampton Driving Simulator, each using varying levels of automation and driver skill. The first was a large-scale study designed to explore the relationship between attention, automaticity, mental workload and performance. Some compelling evidence for malleable attentional resources theory was found, and mental workload interacted with skill level as predicted. From this study, two methodological issues arose which were addressed in the two subsequent experiments. The final study used this methodological information to guide its design. Further support for malleable attentional resources theory was sought by investigating skill differences in response to automation failure. It was found that unskilled drivers were particularly disadvantaged by an underload situation.
University of Southampton
Young, Mark S
f7204378-f076-4b00-a9ae-edc94695abb7
2000
Young, Mark S
f7204378-f076-4b00-a9ae-edc94695abb7
Young, Mark S
(2000)
Attention, automaticity, and automation : New perspectives on mental underload and performance.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
Commentators on vehicle technology predict that in 100 years, cars will be fully automated, and the traditional concept of a driver will be redundant. Some vehicle devices that represent a first step towards this goal are already on the market, and others are due to follow in the near future. Whilst vehicle automation is not unfamiliar on today's roads, new technologies such as ACC and AS have the potential to reduce driver mental workload in addition to relieving physical workload. Previous research suggests, though, that reducing mental workload is not necessarily a good thing. It is widely believed that mental underload can be detrimental to performance. Despite the wealth of literature establishing a relation between underload and performance decrements, there are very few attempts to explain why this may be the case. The present thesis reviews theories of attention and skill development, as well as the literature on mental workload and automation, to synthesise a new explanation for the effect of mental underload on performance. A theory of malleable attentional resources is proposed to account for the effects of underload, and consideration is given to how the development of automaticity may influence performance in underload situations. It is hypothesised that attentional capacity can shrink in response to reduced task demands, and that performance in such underload situations is dependent on the level of operator skill.
Four experiments were conducted in the Southampton Driving Simulator, each using varying levels of automation and driver skill. The first was a large-scale study designed to explore the relationship between attention, automaticity, mental workload and performance. Some compelling evidence for malleable attentional resources theory was found, and mental workload interacted with skill level as predicted. From this study, two methodological issues arose which were addressed in the two subsequent experiments. The final study used this methodological information to guide its design. Further support for malleable attentional resources theory was sought by investigating skill differences in response to automation failure. It was found that unskilled drivers were particularly disadvantaged by an underload situation.
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Published date: 2000
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Local EPrints ID: 466997
URI: http://eprints.soton.ac.uk/id/eprint/466997
PURE UUID: f43b979a-e68b-4943-9f09-d557c343aa19
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Date deposited: 05 Jul 2022 08:06
Last modified: 16 Mar 2024 20:55
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Author:
Mark S Young
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