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An enhanced vehicle control model for assessing highly automated driving safety

机译:用于评估高度自动化驾驶安全性的增强车辆控制模型

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Automation has been changing the types and causes of hazards, and influencing the way in which users interact with complex systems, particularly challenging the notion of human control as a primary basis for hazard mitigation. In this paper, we explore this challenge and use an automotive driving example to examine the distributed nature of the driving task.We define an Enhanced Vehicle Control Model (VCM) that extends the notion of controllability and joint cognition for highly automated tasks. We apply the model to three contemporary driver assistance systems by undertaking a scenario-based evaluation. As a conceptual model, the Enhanced VCM shows potential to proactively identify the hazard causes associated with a joint cognitive control. However, to provide utility and to become an effective tool for the system analyst, an accompanying methodology is needed. This is the focus of our ongoing research.
机译:自动化一直在改变危险的类型和原因,并影响用户与复杂系统交互的方式,特别是将人类控制的概念挑战为危害缓解的主要基础。在本文中,我们探讨了这一挑战,并使用汽车驾驶示例来检查驾驶任务的分布性质。我们定义了增强的车辆控制模型(VCM),其扩展了可控性的概念和高度自动化任务的联合认知。我们通过进行基于场景的评估,将模型应用于三个当代驾驶员辅助系统。作为一个概念模型,增强的VCM显示了主动识别与联合认知控制相关的危害原因的可能性。但是,要提供实用性并成为系统分析师的有效工具,需要伴随的方法。这是我们正在进行的研究的重点。

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