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Modeling takeover time based on non-driving-related task attributes in highly automated driving
Applied Ergonomics ( IF 3.2 ) Pub Date : 2020-12-18 , DOI: 10.1016/j.apergo.2020.103343
Sol Hee Yoon 1 , Seul Chan Lee 2 , Yong Gu Ji 1
Affiliation  

This study aims to investigate the effects of non-driving-related tasks (NDRTs) on the transition of control in highly automated driving (HAD) by investigating the effects of NDRT physical, visual, and cognitive attributes during transition of control. A conceptual model of the takeover process is proposed by dividing this process into motor and mental reactions. A laboratory experiment was conducted to evaluate the effects of each NDRT attribute on the corresponding stage of the process of taking over control. A prediction model was developed using the results of multiple linear regression analysis. Additionally, a validation experiment with nine NDRTs and a baseline condition was conducted to determine the extent to which the developed model explains the takeover time for each NDRT condition. The results showed that the timing aspects of the transition of control in HAD largely consist of participant motor reactions that are affected by the physical attributes of NDRTs.



中文翻译:

高度自动驾驶中基于非驾驶相关任务属性的接管时间建模

本研究旨在通过研究 NDRT 物理、视觉和认知属性在控制转换过程中的影响,研究非驾驶相关任务 (NDRT) 对高度自动驾驶 (HAD) 控制转换的影响。接管过程的概念模型通过将该过程分为运动反应和心理反应来提出。进行了一项实验室实验,以评估每个 NDRT 属性对接管控制过程的相应阶段的影响。使用多元线性回归分析的结果开发了预测模型。此外,还对九个 NDRT 和基线条件进行了验证实验,以确定开发的模型在多大程度上解释了每个 NDRT 条件的接管时间。

更新日期:2020-12-18
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