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运用模糊信号检测理论来确定为何经验丰富且经过训练的驾驶员在危险感知测试中的反应比新手更快。

Using fuzzy signal detection theory to determine why experienced and trained drivers respond faster than novices in a hazard perception test.

作者信息

Wallis Thomas S A, Horswill Mark S

机构信息

School of Psychology, University of Queensland, St. Lucia, Queensland 4072, Australia.

出版信息

Accid Anal Prev. 2007 Nov;39(6):1177-85. doi: 10.1016/j.aap.2007.03.003. Epub 2007 Apr 5.

Abstract

Drivers' hazard perception ability, as measured in video-based simulations, correlates with crash involvement, improves with experience and can be trained. We propose two alternative signal detection models that could describe individual differences in this skill. The first model states that novice drivers are poorer at discriminating more hazardous from less hazardous situations than experienced drivers. The second model proposes that novice drivers require a higher threshold of danger to be present before they notice a situation is hazardous or before they are willing to classify a situation as hazardous. We applied a technique involving fuzzy signal detection analysis to differentiate between these two models when comparing novice and experienced drivers, and trained and untrained drivers, in various video-based hazard perception measures. The data favored the second model.

摘要

在基于视频的模拟测试中所测量的驾驶员危险感知能力,与撞车事故发生率相关,会随着经验的增加而提高,并且可以通过训练得到提升。我们提出了两种可供选择的信号检测模型,它们能够描述这项技能中的个体差异。第一个模型指出,与经验丰富的驾驶员相比,新手驾驶员在区分危险程度较高和较低的情况时能力较差。第二个模型提出,新手驾驶员在注意到一种情况具有危险性之前,或者在愿意将一种情况归类为危险情况之前,需要更高的危险阈值。在比较新手和经验丰富的驾驶员以及经过训练和未经过训练的驾驶员在各种基于视频的危险感知测量中的表现时,我们应用了一种涉及模糊信号检测分析的技术来区分这两种模型。数据支持了第二个模型。

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