Young Mark S, Stanton Neville A
Railway Safety, Evergreen House, London, England.
Hum Factors. 2002 Fall;44(3):365-75. doi: 10.1518/0018720024497709.
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.
本文提出了一种新理论来解释负荷不足对绩效的影响。可塑注意力资源理论假定，注意力容量会根据任务需求的变化而改变大小。因此，与心理负荷不足相关的绩效下降可以用缺乏适当的注意力资源来解释。这些提议在一项驾驶模拟器实验中得到了探究。车辆自动化程度被设置为4个水平，并通过一项次要任务来评估心理负荷。还记录了眼动情况，以确定注意力容量是否随心理负荷而变化。结果显示，与某些自动化水平相关的心理负荷明显下降。不过，最引人注目的是眼动记录得出的结果，这些结果表明注意力容量与心理负荷水平直接相关。这些数据充分支持了新理论的预测。可塑注意力资源理论表明，未来的车辆设计师应将其技术应用于驾驶员支持系统，而非用于自动化以取代驾驶员。本文就该理论对注意力容量模型以及未来车辆系统设计的影响进行了讨论。
