在自动驾驶中使用人机界面传递反馈

IF 2.2 Q3 ENGINEERING, INDUSTRIAL Journal of Cognitive Engineering and Decision Making Pub Date : 2022-03-01 DOI:10.1177/15553434221076827
E. Shull, John G. Gaspar, D. McGehee, Rose Schmitt
{"title":"在自动驾驶中使用人机界面传递反馈","authors":"E. Shull, John G. Gaspar, D. McGehee, Rose Schmitt","doi":"10.1177/15553434221076827","DOIUrl":null,"url":null,"abstract":"The next decade will see a rapid increase in the prevalence of partial vehicle automation, specifically conditional automation (i.e., SAE level 3; SAE, 2018). In conditional automation, the expectation is that the user is still receptive to takeover and can disengage while the automation is active, but as the automation approaches its operational limits, or the end of its operational design domain, it issues a request to intervene and the user is expected to retake control. A human–machine interface (HMI) that can safely and effectively transition control is therefore very important. This simulator study investigated how features of the HMI design, specifically feedback about the confidence (i.e., current capability) of the automation influenced transition of control. Participants were assigned to one of three conditions, which received varying amounts of visual and auditory feedback regarding the automation’s confidence. Findings suggest 3-stage auditory-visual feedback about the automation’s confidence may improve subsequent takeover performance compared to 3-stage visual and a control group without feedback. This research demonstrates the potential value of providing more insight into automated feature performance in conditional automation.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":"16 1","pages":"29 - 42"},"PeriodicalIF":2.2000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Using Human–Machine Interfaces to Convey Feedback in Automated Driving\",\"authors\":\"E. Shull, John G. Gaspar, D. McGehee, Rose Schmitt\",\"doi\":\"10.1177/15553434221076827\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The next decade will see a rapid increase in the prevalence of partial vehicle automation, specifically conditional automation (i.e., SAE level 3; SAE, 2018). In conditional automation, the expectation is that the user is still receptive to takeover and can disengage while the automation is active, but as the automation approaches its operational limits, or the end of its operational design domain, it issues a request to intervene and the user is expected to retake control. A human–machine interface (HMI) that can safely and effectively transition control is therefore very important. This simulator study investigated how features of the HMI design, specifically feedback about the confidence (i.e., current capability) of the automation influenced transition of control. Participants were assigned to one of three conditions, which received varying amounts of visual and auditory feedback regarding the automation’s confidence. Findings suggest 3-stage auditory-visual feedback about the automation’s confidence may improve subsequent takeover performance compared to 3-stage visual and a control group without feedback. This research demonstrates the potential value of providing more insight into automated feature performance in conditional automation.\",\"PeriodicalId\":46342,\"journal\":{\"name\":\"Journal of Cognitive Engineering and Decision Making\",\"volume\":\"16 1\",\"pages\":\"29 - 42\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cognitive Engineering and Decision Making\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/15553434221076827\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Engineering and Decision Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/15553434221076827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 3

摘要

未来十年,部分车辆自动化,特别是条件自动化的普及率将迅速上升(即SAE 3级;SAE,2018)。在条件自动化中,期望用户仍然接受接管,并且可以在自动化活动时脱离,但随着自动化接近其操作极限,或其操作设计领域的结束,它发出干预请求,并且期望用户重新获得控制。因此,能够安全有效地转换控制的人机界面(HMI)非常重要。该模拟器研究调查了HMI设计的特征,特别是关于自动化的置信度(即当前能力)的反馈如何影响控制的转变。参与者被分配到三种条件中的一种,这些条件接收到关于自动化信心的不同数量的视觉和听觉反馈。研究结果表明,与没有反馈的3阶段视觉和对照组相比,关于自动化信心的3阶段听觉-视觉反馈可能会提高后续接管性能。这项研究证明了在条件自动化中提供更多关于自动化特征性能的见解的潜在价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Using Human–Machine Interfaces to Convey Feedback in Automated Driving
The next decade will see a rapid increase in the prevalence of partial vehicle automation, specifically conditional automation (i.e., SAE level 3; SAE, 2018). In conditional automation, the expectation is that the user is still receptive to takeover and can disengage while the automation is active, but as the automation approaches its operational limits, or the end of its operational design domain, it issues a request to intervene and the user is expected to retake control. A human–machine interface (HMI) that can safely and effectively transition control is therefore very important. This simulator study investigated how features of the HMI design, specifically feedback about the confidence (i.e., current capability) of the automation influenced transition of control. Participants were assigned to one of three conditions, which received varying amounts of visual and auditory feedback regarding the automation’s confidence. Findings suggest 3-stage auditory-visual feedback about the automation’s confidence may improve subsequent takeover performance compared to 3-stage visual and a control group without feedback. This research demonstrates the potential value of providing more insight into automated feature performance in conditional automation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.60
自引率
10.00%
发文量
21
期刊最新文献
Is the Pull-Down Effect Overstated? An Examination of Trust Propagation Among Fighter Pilots in a High-Fidelity Simulation A Taxonomy for AI Hazard Analysis Understanding Automation Failure Integrating Function Allocation and Operational Event Sequence Diagrams to Support Human-Robot Coordination: Case Study of a Robotic Date Thinning System Adapting Cognitive Task Analysis Methods for Use in a Large Sample Simulation Study of High-Risk Healthcare Events.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1