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Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems

机译:人为错误分类法应用于驾驶:通用驾驶员错误分类法及其对智能交通系统的影响

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摘要

Recent research indicates that driver error contributes to up to 75% of all roadway crashes. Despite this, only relatively little is currently known about the types of errors that drivers make and of the causal factors that contribute to these errors being made. This article presents an overview of the literature on human error in road transport. In particular, the work of three pioneers of human error research, Norman, Reason and Rasmussen, is scrutinised. An overview of the research on driver error follows, to consider the different types of errors that drivers make. It was found that all but one of these does not use a human error taxonomy. A generic driver error taxonomy is therefore proposed based upon the dominant psychological mechanisms thought to be involved. These mechanisms are: perception, attention, situation assessment, planning and intention, memory and recall, and action execution. In addition, a taxonomy of road transport error causing factors, derived from the review of the driver error literature, is also presented. In conclusion to this article, a range of potential technological solutions that could be used to either prevent, or mitigate, the consequences of the driver errors identified are specified.
机译:最近的研究表明,驾驶员错误占所有道路交通事故的75%。尽管如此,对于驾驶员造成的错误类型以及造成这些错误的因果关系,目前知之甚少。本文概述了道路运输中人为错误的文献。特别是,对人为错误研究的三个先驱者Norman,Reason和Rasmussen的工作进行了审查。接下来,对驱动程序错误的研究进行了概述,以考虑驱动程序造成的不同类型的错误。已经发现,除了其中之一以外,所有其他人都没有使用人为错误分类法。因此,基于被认为涉及的主要心理机制,提出了一种通用的驾驶员错误分类法。这些机制是:感知,关注,状况评估,计划和意图,记忆和回忆以及动作执行。此外,还介绍了根据驾驶员错误文献回顾得出的公路运输错误引起因素的分类法。在本文的总结中,详细说明了可用于预防或减轻所确定的驾驶员错误后果的一系列潜在技术解决方案。

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