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Driver Emotion Recognition for Intelligent Vehicles: A Survey

机译：智能车辆的驾驶情感认同：调查

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摘要

Driving can occupy a large portion of daily life and often can elicit negative emotional states like anger or stress, which can significantly impact road safety and long-term human health. In recent decades, the arrival of new tools to help recognize human affect has inspired increasing interest in how to develop emotion-aware systems for cars. To help researchers make needed advances in this area, this article provides a comprehensive literature survey of work addressing the problem of human emotion recognition in an automotive context. We systematically review the literature back to 2002 and identify 63 peer-review published articles on this topic. We overview each study's methodology to measure and recognize emotions in the context of driving. Across the literature, we find a strong preference toward studying emotional states associated with high arousal and negative valence, monitoring the different states with cardiac, electrodermal activity, and speech signals, and using supervised machine learning to automatically infer the underlying human affective states. This article summarizes the existing work together with publicly available resources (e.g., datasets and tools) to help new researchers get started in this field. We also identify new research opportunities to help advance progress for improving driver emotion recognition.
机译：驾驶可以占据日常生活的大部分，并且经常可以引起愤怒或压力等负面情绪状态，这可能会显着影响道路安全和长期人类健康。近几十年来，新工具的到来，帮助识别人类影响的灵感来自如何发展汽车情绪感知系统的兴趣。为了帮助研究人员在这一领域进行必要的进展，本文提供了一种全面的文学调查，解决了在汽车背景下的人类情感认知问题的工作。我们系统地审查文献回到2002年，并确定了关于本主题的63个同行评审发布的条款。我们概述了每种研究的方法，以衡量和识别驾驶范围内的情绪。在整个文献中，我们发现了研究与高唤起和消极价相关的情绪状态的强烈偏好，监测有心脏，电寄射活动和语音信号的不同状态，以及使用监督机器学习自动推断潜在的人类情感状态。本文总结了现有的工作以及公开可用的资源（例如，数据集和工具），以帮助新的研究人员在此领域开始。我们还确定了新的研究机会，以帮助提高提高驾驶员情感认可的进展。

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