工作量
任务(项目管理)
认知心理学
自动化
驾驶模拟器
心理学
模拟
计算机科学
应用心理学
人机交互
工程类
机械工程
系统工程
操作系统
作者
Mark S. Young,Neville A. Stanton
出处
期刊:Human Factors
[SAGE]
日期:2002-09-01
卷期号:44 (3): 365-375
被引量:378
标识
DOI:10.1518/0018720024497709
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI