Assessing How Driving Self-Efficacy Influences Situational Trust in Driver Assist Technologies

情境伦理学 渐晕 形势意识 自动化 高级驾驶员辅助系统 计算机科学 多样性(控制论) 人机交互 心理学 工程类 社会心理学 机械工程 航空航天工程 人工智能
作者
James C. Ferraro,Mustapha Mouloua
出处
期刊:Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting [SAGE Publishing]
卷期号:66 (1): 1260-1264 被引量:4
标识
DOI:10.1177/1071181322661476
摘要

As the movement toward fully autonomous driving continues, it is critical to assess factors that may impact how drivers interact with and perform in conjunction with automated driving systems. The trust drivers place in the driver assist technologies can impact how effectively these systems are utilized. Human factors research has found a variety of factors related to the environment, the system, and the user that influence trust in automated systems. The current study was designed to assess how situational factors influence how drivers trust different driver assist features, and how driving self-efficacy impacts this relationship. 101 participants reported situational trust scores based on 10 vignette traffic scenarios that described driving in high or low complexity situations while using one of five driver assist features. It was hypothesized that situation and automation-related factors would influence participants’ trust. Results indicated a significant interaction between the complexity of the driving scenario and the different driver assist features. Additional results indicated self-efficacy impacted relationships between the driver assist technologies and trust. These findings are consistent with previous results related to trust and use of automation and have implications for researchers interested in how drivers interact with current and emerging driving technologies. These results can be applied to the development of automated driving systems, informing decisions in the design of future automated vehicles.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
HZH完成签到,获得积分10
刚刚
端庄不愁发布了新的文献求助10
刚刚
xiaocheche发布了新的文献求助10
1秒前
科研通AI2S应助agony采纳,获得10
1秒前
1秒前
FashionBoy应助kdc采纳,获得10
3秒前
3秒前
隐形曼青应助Nov采纳,获得10
4秒前
ydy完成签到,获得积分10
4秒前
lsl发布了新的文献求助10
4秒前
科研通AI6.3应助少卿采纳,获得10
5秒前
又或发布了新的文献求助10
6秒前
达瓦里氏完成签到 ,获得积分10
7秒前
8秒前
9秒前
9秒前
pz发布了新的文献求助10
13秒前
Cqy完成签到,获得积分20
14秒前
Gamen发布了新的文献求助10
14秒前
vandung发布了新的文献求助10
14秒前
15秒前
FashionBoy应助PPY采纳,获得10
16秒前
yzy应助Huang采纳,获得10
16秒前
Tineobius2025完成签到,获得积分10
17秒前
张欢馨应助拾三采纳,获得10
18秒前
垚垚应助ZAC采纳,获得10
18秒前
Owen应助kdc采纳,获得10
18秒前
可可西应助端庄不愁采纳,获得10
19秒前
呼呼不爱噜噜应助Zilliax采纳,获得10
20秒前
21秒前
23秒前
23秒前
24秒前
所所应助清爽莫言采纳,获得10
24秒前
SAVANNAH完成签到,获得积分10
25秒前
25秒前
26秒前
领导范儿应助Gamen采纳,获得10
27秒前
123完成签到,获得积分10
28秒前
28秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Pediatric Dermoscopy Trichoscopy & Onychoscopy 2030
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7576693
求助须知:如何正确求助?哪些是违规求助? 9156229
关于积分的说明 19588131
捐赠科研通 7160518
什么是DOI,文献DOI怎么找? 3265072
关于科研通互助平台的介绍 2430197
邀请新用户注册赠送积分活动 2255690