基于仿真的智能驾驶辅助技术需求发现

A. Gregoriades, M. Pampaka, A. Sutcliffe
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引用次数: 2

摘要

智能驾驶辅助技术(DAT)通过减少驾驶员的工作量或评估驾驶员的注意力来降低事故风险。这类系统旨在将驾驶员的注意力吸引到关键线索上,从而提高决策能力。然而,在某些情况下,这些系统可能会产生负面影响,因为它们会给驱动程序带来额外的信息负载。因此,除了为这样的系统指定功能需求之外,迫切需要解决人的需求。这项工作描述了一种基于仿真的需求发现方法,该方法利用模块化模拟器的优点,为未来的DAT设计建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation-based requirements discovery for smart driver assistive technologies
Smart driver assistive technologies (DAT) have been developed to alleviate accident risk by either reducing driver workload or assessing driver attentiveness. Such systems aim to draw drivers' attention on critical cues that improve decision making. However, in some cases, these systems can have a negative effect due to the extra information load they incur to the driver. Therefore, in addition to specifying the functional requirements for such systems there is an urgent need to address the human requirements. This work describes a simulation-based requirements discovery method that utilises the benefits of a modular simulator that models future designs of DAT.
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