Drivers’ Performance in Non-critical Take-Overs From an Automated Driving System—An On-Road Study

超车 控制(管理) 向导 可用性 运输工程 工程类 模拟 人机交互 毒物控制 绿野仙踪 计算机科学 航空学 计算机安全 应用心理学 人工智能 心理学 万维网 环境卫生 医学
作者
Annie Rydström,Mattias Söderholm Mullaart,Fjollë Novakazi,Mikael Johansson,Alexander Eriksson
出处
期刊:Human Factors [SAGE]
卷期号:65 (8): 1841-1857 被引量:3
标识
DOI:10.1177/00187208211053460
摘要

Objective The objective of this semi-controlled study was to investigate drivers’ performance when resuming control from an Automated Driving System (ADS), simulated through the Wizard of Oz method, in real traffic. Background Research on take-overs has primarily focused on urgent scenarios. This article aims to shift the focus to non-critical take-overs from a system operating in congested traffic situations. Method Twenty drivers drove a selected route in rush-hour traffic in the San Francisco Bay Area, CA, USA. During the drive, the ADS became available when predetermined availability conditions were fulfilled. When the system was active, the drivers were free to engage in non-driving related activities. Results The results show that drivers’ transition time goes down with exposure, making it reasonable to assume that some experience is required to regain control with comfort and ease. The novel analysis of after-effects of automated driving on manual driving performance implies that the after-effects were close to negligible. Observational data indicate that, with exposure, a majority of the participants started to engage in non-driving related activities to some extent, but it is unclear how the activities influenced the take-over performance. Conclusion The results indicate that drivers need repeated exposure to take-overs to be able to fully resume manual control with ease. Application Take-over signals (e.g., visuals, sounds, and haptics) should be carefully designed to avoid startle effects and the human-machine interface should provide clear guidance on the required take-over actions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
Yulin Yu发布了新的文献求助10
2秒前
3秒前
4秒前
许哲完成签到,获得积分10
4秒前
5秒前
欢喜发布了新的文献求助10
5秒前
许哲发布了新的文献求助10
7秒前
zhangz完成签到,获得积分10
7秒前
cg发布了新的文献求助10
7秒前
8秒前
8秒前
CodeCraft应助哈哈哈采纳,获得10
9秒前
9秒前
9秒前
11秒前
fzj完成签到 ,获得积分10
12秒前
12秒前
14秒前
shelley发布了新的文献求助10
14秒前
14秒前
舒心的涔雨完成签到,获得积分10
14秒前
充电宝应助yuki采纳,获得10
14秒前
15秒前
崔小可完成签到,获得积分10
16秒前
16秒前
17秒前
M998发布了新的文献求助10
17秒前
Chirstina完成签到,获得积分10
19秒前
两半桃花发布了新的文献求助10
19秒前
A1234567完成签到,获得积分10
20秒前
罗山柳发布了新的文献求助10
20秒前
ycg完成签到,获得积分10
20秒前
蔡坤佑完成签到,获得积分10
20秒前
青岚发布了新的文献求助10
21秒前
21秒前
林非鹿发布了新的文献求助10
22秒前
陶醉访文发布了新的文献求助10
22秒前
23秒前
888888888发布了新的文献求助10
23秒前
高分求助中
Sustainable Land Management: Strategies to Cope with the Marginalisation of Agriculture 1000
Corrosion and Oxygen Control 600
Yaws' Handbook of Antoine coefficients for vapor pressure 500
Python Programming for Linguistics and Digital Humanities: Applications for Text-Focused Fields 500
行動データの計算論モデリング 強化学習モデルを例として 500
Johann Gottlieb Fichte: Die späten wissenschaftlichen Vorlesungen / IV,1: ›Transzendentale Logik I (1812)‹ 400
The role of families in providing long term care to the frail and chronically ill elderly living in the community 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2554165
求助须知:如何正确求助?哪些是违规求助? 2179056
关于积分的说明 5617227
捐赠科研通 1900155
什么是DOI,文献DOI怎么找? 948865
版权声明 565554
科研通“疑难数据库(出版商)”最低求助积分说明 504484