ViE-Take:一个视觉驱动的多模式数据集,用于探索自动驾驶的接管安全的情感景观
Yantong Wang1,2, Yu Gu3, Tong Quan2
1School of Biomedical Engineering, Anhui Medical University, Hefei, China.
Research (Washington, D.C.)
|March 17, 2025
概括
这项研究介绍了ViE-Take,这是一个用于分析自动驾驶汽车接管期间驾驶员情绪的新型数据集. 调查结果显示,情绪对接管安全有影响,基于视觉的AI显示了性能预测的潜力.
科学领域:
- 智能运输系统 智能运输系统
- 人与计算机的交互
- 情感计算是一种情感计算.
背景情况:
- 自动驾驶汽车的安全性至关重要,驾驶员的情绪会影响接管性能.
- 现有的数据集缺乏情绪意识数据,限制了该领域的研究.
- 具有先进自动驾驶系统的新能源汽车需要了解驾驶员的反应.
研究的目的:
- 介绍ViE-Take,这是第一个以视觉驱动的数据集,用于自动驾驶接管中的情感景观.
- 能够全面探索情绪对驾驶员接管性能的影响.
- 提供深度学习模型来预测接管准备,反应时间和质量.
主要方法:
- 开发了ViE-Take数据集,使用多源情绪诱导和多模式驾驶员数据收集.
- 整合了多维情感注释以进行详细分析.
- 训练并验证了四种深度学习模型用于收购业绩预测.
主要成果:
- 情绪对接管绩效表现出多样化,有时甚至是反直觉的影响.
- 社交媒体的剪辑有效地引起情绪,帮助情绪调节策略.
- 基于视觉的深度学习模型证明了预测收购绩效的可行性和潜力.
结论:
- ViE-Take数据集促进了对智能交通中的情感感知接管安全性的研究.
- 情绪识别和调节对于提高自动驾驶安全至关重要.
- 基于视觉的AI对实时驾驶员监控和安全应用具有重大前景.
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