Distraction pattern classification and comparisons under different conditions in the full-touch HMI mode

分散注意力 任务(项目管理) 驾驶模拟器 计算机科学 模拟 心理学 工程类 认知心理学 系统工程
作者
Xia Zhao,Li Zhao,Chen Zhao,Chang Wang,Rui Fu
出处
期刊:Displays [Elsevier]
卷期号:78: 102413-102413 被引量:7
标识
DOI:10.1016/j.displa.2023.102413
摘要

Understanding driver distraction patterns is an important part of human–machine interaction (HMI), which is beneficial for the development of control strategies in human–machine co-driving systems. However, comparatively few studies have focused on driver distraction patterns. To address this issue, this study proposes a framework to characterize distraction patterns using glance behavior and manual behavior, and classifies distraction patterns into: aggressive, moderate, and conservative patterns based on real road experiments. Subsequently, differences in distraction behavior and effects on lateral vehicle control ability across distraction pattern groups, as well as distraction behavior differences exhibited by drivers in the same distraction pattern group under different conditions, are analyzed. Firstly, the results show that the aggressive distraction patterns have a smaller number of eyes-off-road (NoEOR) incidences but longer mean single eyes-off-road time (MSEORT), maximum single eyes-off-road time (MaxEORT) and a higher percentage of long eyes-off-road (PoLEOR) incidences than the other patterns. There are slight differences in the single eyes-off-road times (EORTs) between the conservative and moderate patterns and in the manual behavior for the aggressive and moderate distraction patterns. Secondly, the same distraction pattern exhibited by drivers for different road and secondary task conditions has differences in terms of the behavioral performance. Finally, there is few differences in the lateral motion of a vehicle with different distraction patterns. Surprisingly, the standard deviation of the steering wheel angle (SDSWA) is the smallest in the aggressive distraction pattern.
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
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
林结衣完成签到,获得积分10
刚刚
量子星尘发布了新的文献求助10
1秒前
雪白巨人发布了新的文献求助10
1秒前
朴实的虔发布了新的文献求助10
1秒前
细腻的雅山完成签到 ,获得积分10
1秒前
汉堡包应助yg采纳,获得10
2秒前
賢様666发布了新的文献求助10
2秒前
JingjingYao完成签到,获得积分10
2秒前
彭于晏应助liujian采纳,获得10
3秒前
甜茶发布了新的文献求助10
3秒前
幻翎发布了新的文献求助10
3秒前
大模型应助xxx采纳,获得10
3秒前
小新同学发布了新的文献求助10
3秒前
3秒前
YM完成签到,获得积分10
4秒前
princelee完成签到,获得积分10
6秒前
6秒前
桥豆麻袋完成签到,获得积分10
7秒前
fifi发布了新的文献求助10
7秒前
8秒前
长安的荔枝给长安的荔枝的求助进行了留言
8秒前
8秒前
ccyy发布了新的文献求助10
8秒前
丘比特应助开心的又夏采纳,获得10
8秒前
量子星尘发布了新的文献求助10
8秒前
无奈曼云发布了新的文献求助10
9秒前
指沙发布了新的文献求助10
9秒前
10秒前
111完成签到,获得积分10
11秒前
12秒前
2号发布了新的文献求助10
12秒前
12秒前
筱鳴童學发布了新的文献求助10
13秒前
领导范儿应助ZXCVB采纳,获得10
13秒前
陈扬完成签到 ,获得积分20
13秒前
13秒前
15秒前
15秒前
Aurora发布了新的文献求助10
15秒前
一地狗粮发布了新的文献求助10
15秒前
高分求助中
(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
Introduction to strong mixing conditions volume 1-3 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
从k到英国情人 1500
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5727988
求助须知:如何正确求助?哪些是违规求助? 5310720
关于积分的说明 15312703
捐赠科研通 4875267
什么是DOI,文献DOI怎么找? 2618674
邀请新用户注册赠送积分活动 1568332
关于科研通互助平台的介绍 1524966