Suppr超能文献

驾驶员视觉分散接管性能模型及其在时间预算自适应调整中的应用。

Drivers' visual-distracted take-over performance model and its application on adaptive adjustment of time budget.

机构信息

State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, 100084, China; Center for Intelligent Connected Vehicles and Transportation, Tsinghua University, Beijing, 100084, China.

Institute of Industrial Science, The University of Tokyo, Tokyo, 1538505, Japan.

出版信息

Accid Anal Prev. 2021 May;154:106099. doi: 10.1016/j.aap.2021.106099. Epub 2021 Mar 23.

Abstract

There are certain situations that automated driving (AD) systems are still unable to handle, preventing the implementation of Level 5 AD. Thus, a transition of control, colloquially known as take-over of the vehicle, is required when the system sends a take-over request (TOR) upon exiting the operational design domain (ODD). An adaptive TOR along with good take-over performance requires adjusting the time budget (TB) to drivers' visual distraction state, adhering to a reliable visual-distraction-based take-over performance model. Based on a number of driving simulator experiments, the percentage of face orientation to distraction area (PFODA) and time to boundary at take-over timing (TTBT) were proposed to accurately evaluate the degree of visual distraction based on merely face orientation under naturalistic non-driving related tasks (NDRTs) and to evaluate take-over performance, respectively. In order to elucidate the safety boundary, this study also proposed an algorithm to set a suitable minimum value of the TTBT. Finally, a multiple regression model was built to describe the relationship among PFODA, TB and TTBT along with a corrected coefficient of determination of 0.748. Based on the model, this study proposed an adaptive TB adjustment method for the take-over system.

摘要

在某些情况下,自动驾驶(AD)系统仍然无法处理,这阻止了实现 5 级 AD。因此,当系统在退出操作设计域(ODD)时发出接管请求(TOR)时,需要进行控制权的转换,通常称为车辆接管。为了实现自适应 TOR 和良好的接管性能,需要根据驾驶员的视觉分散状态调整时间预算(TB),并遵守可靠的基于视觉分散的接管性能模型。基于大量驾驶模拟器实验,提出了面向分散区域的面部比例(PFODA)和在接管时间的边界到达时间(TTBT),以在自然非驾驶相关任务(NDRTs)下仅根据面部方向准确评估视觉分散程度,并评估接管性能。为了阐明安全边界,本研究还提出了一种算法来设置 TTBT 的合适最小值。最后,建立了一个多元回归模型来描述 PFODA、TB 和 TTBT 之间的关系,校正后的决定系数为 0.748。基于该模型,本研究提出了一种用于接管系统的自适应 TB 调整方法。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验