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老龄化对驾驶决策的影响:一种扩散模型分析。

The effect of aging on decision-making while driving: A diffusion model analysis.

机构信息

Department of Psychology, The Ohio State University.

出版信息

Psychol Aging. 2022 Jun;37(4):441-455. doi: 10.1037/pag0000690. Epub 2022 May 16.

DOI:10.1037/pag0000690
PMID:35575704
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9677511/
Abstract

We present a diffusion model analysis of the effect of aging on decision processes during driving. Our goal was to examine the changes in the underlying components as a function of age and both task and environment difficulty. Younger and older adults performed each of three decision-making tasks while operating a computer-based driving simulator in which the task required a driving action. The first task was a one-choice task in which the response to brake lights turning on was to drive around a lead car. The second and third tasks were two-choice brightness-discrimination tasks in which participants were asked to drive the car to the left/right if there were more black/white pixels in an array of black and white pixels. Results showed that older adults were slower in the one-choice task and made more errors in the two-choice tasks than younger adults. The behavioral data were fitted well by one- and two-choice diffusion models, showing lower evidence accumulation rates (drift rates) in older than younger adults. Moreover, in the two-choice tasks under higher environmental demands, older adults showed a lower decision criterion (boundary separation) to compensate for a slower decision process. Together, the differences we found in the decision components between age groups provided an example of a subtle interaction between speed and accuracy in older versus younger adults, and this demonstrates the utility of this modeling approach in studying age effects in driving. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

摘要

我们呈现了一个扩散模型分析,研究了衰老对驾驶过程中决策的影响。我们的目标是研究随着年龄的增长以及任务和环境难度的变化,潜在成分的变化。年轻和年长的成年人在驾驶模拟器中执行了三个决策任务中的每一个,在这个模拟器中,任务需要进行驾驶操作。第一个任务是一个单一选择任务,当刹车灯亮起时,需要绕过前方车辆。第二个和第三个任务是两个选择的亮度辨别任务,参与者需要根据数组中黑色和白色像素的数量来向左/向右驾驶汽车。结果表明,年长的成年人在单一选择任务中较慢,在两个选择任务中犯错较多。行为数据很好地拟合了一个和两个选择的扩散模型,表明年长的成年人的证据积累率(漂移率)低于年轻的成年人。此外,在环境要求较高的两个选择任务中,年长的成年人表现出较低的决策标准(边界分离),以补偿较慢的决策过程。总的来说,我们在年龄组之间的决策成分中发现的差异,为在速度和准确性方面,年老的成年人与年轻的成年人之间的微妙相互作用提供了一个例子,这证明了这种建模方法在研究驾驶中的年龄效应方面的实用性。

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Sci Rep. 2019 Aug 2;9(1):11224. doi: 10.1038/s41598-019-47624-4.
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