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Emotion on the Road-Necessity, Acceptance, and Feasibility of Affective Computing in the Car

机译:情感情感在汽车上的必要性,接受性和可行性

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摘要

Besides reduction of energy consumption, which implies alternate actuation and light construction, the main research domain in automobile development in the near future is dominated by driver assistance and natural driver-car communication. The ability of a car to understand natural speech and provide a human-like driver assistance system can be expected to be a factor decisive for market success on par with automatic driving systems. Emotional factors and affective states are thereby crucial for enhanced safety and comfort. This paper gives an extensive literature overview on work related to influence of emotions on driving safety and comfort, automatic recognition, control of emotions, and improvement of in-car interfaces by affect sensitive technology. Various use-case scenarios are outlined as possible applications for emotion-oriented technology in the vehicle. The possible acceptance of such future technology by drivers is assessed in a Wizard-Of-Oz user study, and feasibility of automatically recognising various driver states is demonstrated by an example system for monitoring driver attentiveness. Thereby an accuracy of 91.3% is reported for classifying in real-time whether the driver is attentive or distracted.
机译:除了减少能耗(这意味着交替执行和轻巧的构造)之外,在不久的将来,汽车开发的主要研究领域是驾驶员辅助和自然的驾驶员与汽车之间的通信。与自动驾驶系统相比,汽车理解自然语言并提供类似人的驾驶员辅助系统的能力将成为决定市场成功的决定性因素。因此,情绪因素和情感状态对于增强安全性和舒适性至关重要。本文对涉及情绪对驾驶安全性和舒适性的影响,自动识别,情绪控制以及通过影响敏感技术改善车内界面的工作进行了广泛的文献综述。概述了各种用例场景作为车辆中面向情感技术的可能应用。在《绿野仙踪》用户研究中评估了驾驶员对此类未来技术的可能接受,并且通过用于监视驾驶员注意力的示例系统演示了自动识别各种驾驶员状态的可行性。因此,报告的准确度为91.3%,可实时分类驾驶员是否专心或专心。

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  • 来源
    《Advances in human-computer interaction》 |2010年第2010期|p.4.1-4.17|共17页
  • 作者单位

    Institute for Human-Machine Communication, Technische Universitaet Muenchen, 80333 Muenchen, Germany;

    Institute for Human-Machine Communication, Technische Universitaet Muenchen, 80333 Muenchen, Germany;

    Institute for Human-Machine Communication, Technische Universitaet Muenchen, 80333 Muenchen, Germany;

    Institute for Human-Machine Communication, Technische Universitaet Muenchen, 80333 Muenchen, Germany;

    Human Factors Institute, Universitaet der Bundeswehr Muenchen, 85577 Neubiberg, Germany;

    Human Factors Institute, Universitaet der Bundeswehr Muenchen, 85577 Neubiberg, Germany;

    Continental Automotive GmbH, Interior BU Infotainment & Connectivity, Advanced Development and Innovation, 93055 Regensburg, Germany;

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