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Physiological Characteristics and Nonparametric Test for Master-Slave Driving Task's Mental Workload Evaluation in Mountain Area Highway at Night

机译:山区高速公路山区高速公路船舶驾驶任务的生理特性及非参数试验

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摘要

With the rapid development of advanced mobile intelligent terminals, driving tasks are diverse, and new traffic safety problems occur. We propose a new research on physiological characteristics and nonparametric tests for the master-slave driving task, especially for evaluation of drivers' mental workload in mountain area highway in nighttime scenario. First, we establish the experimental platform based driving simulator and design the master-slave driving task. Second, based on the physiological data and subjective evaluation for mental workload, we use statistical methods to composite the physical changes evolution analysis in a driving simulator. Finally, we finished nonparametric test of the drivers' psychological load and road test. The results show that in compassion with the daytime scenario, drivers should pay much effort to driving skills and risk identification in the nighttime scenario. Thus, in the same driving condition, drivers should bear the higher level of mental workload, and it has been subjected to even greater pressures and intensity of emotions.
机译:随着先进的移动智能终端的快速发展,驾驶任务是多样化的,并且发生了新的交通安全问题。我们为主奴隶驾驶任务的生理特性和非参数测试提出了新的研究,特别是在夜间场景中评估山区高速公路中的司机心理工作量。首先,我们建立了基于实验平台的驾驶模拟器,并设计了主从驾驶任务。其次,根据生理数据和心理工作量的主观评估,我们使用统计方法来复合驾驶模拟器中的物理变化演化分析。最后,我们完成了司机心理负荷和道路测试的非参数测试。结果表明,在与日间方案的同情中,司机应该在夜间情景中驾驶技能和风险识别。因此,在相同的驾驶条件下,司机应该承担更高水平的心理工作量,并且已经受到更大的压力和情绪强度。

著录项

  • 来源
    《Journal of Advanced Transportation》 |2019年第5期|2061532.1-2061532.11|共11页
  • 作者单位

    Guangdong Commun Polytech Sch Transportat & Econ Management Guangzhou 510650 Guangdong Peoples R China;

    South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510640 Guangdong Peoples R China;

    South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510640 Guangdong Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 21:43:35

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