Suppr超能文献

在三级自动化驾驶模拟中探索驾驶员静止注视熵与态势感知之间的关系。

Exploring the Relationship Between Drivers' Stationary Gaze Entropy and Situation Awareness in a Level-3 Automation Driving Simulation.

作者信息

Ding Wen, Murzello Yovela, Cao Shi, Samuel Siby

机构信息

University of Waterloo, ON, Canada.

出版信息

Proc Hum Factors Ergon Soc Annu Meet. 2024 Sep;68(1):879-884. doi: 10.1177/10711813241275910. Epub 2024 Aug 29.

Abstract

The transition period from automation to manual, known as the takeover process, presents challenges for drivers due to the deficiency in collecting requisite contextual information. The current study collected drivers' eye movement in a simulated takeover experiment, and their Situation Awareness (SA) was assessed using the Situation Awareness Global Assessment Technique (SAGAT) method. The drivers' Stationary Gaze Entropy (SGE) was calculated based on the percentages of time they spent on six pre-defined Areas of Interests (AOIs). Three critical time windows were extracted by using the takeover alert time spot and the hazard perceived time spot. The result indicated that drivers with higher SAGAT scores would spread their attention among multiple AOIs. Also, drivers' SGE and SA have a linear relationship only at the last time window (hazard perceived to the end) wherein SGE potentially functions as an evaluative metric for assessing SA in the future.

摘要

从自动化到手动操作的过渡阶段,即所谓的接管过程,由于在收集必要的情境信息方面存在不足,给驾驶员带来了挑战。当前的研究在模拟接管实验中收集了驾驶员的眼动数据,并使用情境意识全球评估技术(SAGAT)方法评估了他们的情境意识(SA)。驾驶员的静态注视熵(SGE)是根据他们在六个预定义兴趣区域(AOI)上花费的时间百分比计算得出的。通过使用接管警报时间点和危险感知时间点提取了三个关键时间窗口。结果表明,SAGAT得分较高的驾驶员会将注意力分散到多个AOI上。此外,驾驶员的SGE和SA仅在最后一个时间窗口(从危险感知到结束)存在线性关系,其中SGE可能在未来作为评估SA的一种评估指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d268/11655270/e76750013ccb/10.1177_10711813241275910-fig1.jpg

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