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驾驶员在公共道路自动驾驶时接管请求前后的视觉注意力。

Driver Visual Attention Before and After Take-Over Requests During Automated Driving on Public Roads.

机构信息

Chalmers University of Technology, Gothenburg, Sweden and Volvo Cars, Gothenburg, Sweden.

出版信息

Hum Factors. 2024 Feb;66(2):336-347. doi: 10.1177/00187208221093863. Epub 2022 Jun 16.

DOI:10.1177/00187208221093863
PMID:35708240
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10757385/
Abstract

OBJECTIVE

This study aims to understand drivers' visual attention before and after take-over requests during automated driving (AD), when the vehicle is fully responsible for the driving task on public roads.

BACKGROUND

Existing research on transitions of control from AD to manual driving has mainly focused on take-over times. Despite its relevance for vehicle safety, drivers' visual attention has received little consideration.

METHOD

Thirty participants took part in a Wizard of Oz study on public roads. Drivers' visual attention was analyzed before and after four take-over requests. Visual attention during manual driving was also recorded to serve as a baseline for comparison.

RESULTS

During AD, the participants showed reduced visual attention to the forward road and increased duration of single off-road glances compared to manual driving. In response to take-over requests, the participants looked away from the forward road toward the instrument cluster. Levels of visual attention towards the forward road did not return to the levels observed during manual driving until after 15 s had passed.

CONCLUSION

During AD, drivers may look toward non-driving related task items (e.g., mobile phone) instead of forward. Further, when a transition of control is required, drivers may take over control before they are aware of the driving environment or potential threat(s). Thus, it cannot be assumed that drivers are ready to respond to events shortly after the take-over request.

APPLICATION

It is important to consider the effect of the design of take-over requests on drivers' visual attention alongside take-over times.

摘要

目的

本研究旨在了解自动驾驶(AD)中车辆完全负责道路行驶任务时,接管请求前后驾驶员的视觉注意情况。

背景

现有关于 AD 到手动驾驶的控制权转换的研究主要集中在接管时间上。尽管这与车辆安全相关,但驾驶员的视觉注意受到的关注较少。

方法

30 名参与者在公共道路上进行了“绿野仙踪”研究。分析了四次接管请求前后驾驶员的视觉注意情况。还记录了手动驾驶期间的视觉注意情况,作为比较的基线。

结果

在 AD 期间,与手动驾驶相比,参与者对前方道路的视觉注意减少,单次看路外的持续时间增加。响应接管请求时,参与者将目光从前方道路移至仪表板。直到 15 秒过去,对前方道路的视觉注意水平才恢复到手动驾驶时观察到的水平。

结论

在 AD 期间,驾驶员可能会看向与驾驶无关的任务项目(例如手机),而不是看向前方。此外,当需要进行控制权转换时,驾驶员可能会在意识到驾驶环境或潜在威胁之前接管控制。因此,不能假设驾驶员在接到接管请求后不久就能准备好应对事件。

应用

考虑到接管请求对驾驶员视觉注意的影响以及接管时间,这一点很重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/af58594e31fd/10.1177_00187208221093863-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/a23bc8111f83/10.1177_00187208221093863-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/6912ac4cba96/10.1177_00187208221093863-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/c7c079616cda/10.1177_00187208221093863-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/fb4f3b1c8e2b/10.1177_00187208221093863-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/af58594e31fd/10.1177_00187208221093863-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/a23bc8111f83/10.1177_00187208221093863-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/6912ac4cba96/10.1177_00187208221093863-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/c7c079616cda/10.1177_00187208221093863-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/fb4f3b1c8e2b/10.1177_00187208221093863-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/754a/10757385/af58594e31fd/10.1177_00187208221093863-fig5.jpg

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本文引用的文献

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Hum Factors. 2019 Jun;61(4):642-688. doi: 10.1177/0018720819829572. Epub 2019 Mar 4.
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Noncritical State Transitions During Conditionally Automated Driving on German Freeways: Effects of Non-Driving Related Tasks on Takeover Time and Takeover Quality.
条件自动驾驶高速公路上的非关键状态转换:非驾驶相关任务对接管时间和接管质量的影响。
Hum Factors. 2019 Jun;61(4):596-613. doi: 10.1177/0018720818824002. Epub 2019 Jan 28.
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Automation Expectation Mismatch: Incorrect Prediction Despite Eyes on Threat and Hands on Wheel.自动化期望不匹配:尽管眼睛盯着威胁,手放在方向盘上,但预测仍不准确。
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