Objective Metrics for Assessing Visual Complexity of Vehicle Dashboards: A Machine-Learning Based Study

doi:10.1007/978-3-031-35908-8_8

PSYCH OpenIR

	Objective Metrics for Assessing Visual Complexity of Vehicle Dashboards: A Machine-Learning Based Study
	Huizhi Bai ; Zhizi Liu ; Ziqi Fu,; Zihao Liu ; Huihui Zhang ; Honghai Zhu ; Liang Zhang
第一作者	Huizhi Bai
通讯作者邮箱	zhang, liang
心理所单位排序	1
摘要	Dashboard is a central component of an in-vehicle information system (IVIS), and plays a crucial role in providing drivers with key information related but not limited to driving. With the expansion of the IVIS features, modern dashboards additionally integrate various new elements, which often leads to an increase in their visual complexity. Since high visual complexity of the dashboards threatens driving safety and performance, it is essential for researchers and designers to understand what objective features of the dashboards are related to their perceived visual complexity (PVC) so as to establish more cognitively efficient dashboards. In the present study, we refined the objective metrics of assessing visual complexity proposed in previous research and added two new dimensions, colors and animation, to better characterize recent development in the dashboard displays. We then utilized the indicators in the metrics to predict the dashboard PVC. Machine learning was innovatively applied, and the models were found to have stable performance. The study contributes reliable metrics and novel methodology to evaluate the visual complexity of the dashboards for the reference of future studies.
关键词	Perceived visual complexity Vehicle dashboard Machine learning models Human-vehicle interface design
	2023
语种	英语
DOI	10.1007/978-3-031-35908-8_8
发表期刊	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN	0302-9743
卷号	14049 页码:103-113
期刊论文类型	综述
收录类别	EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.psych.ac.cn/handle/311026/45285
专题	中国科学院心理研究所
作者单位	1.Institute of Psychology, Chinese Academy of Sciences, Beijing, China 2.Chongqing Changan Automobile Co., Chongqing, China 3.Department of Cognitive Science, McGill University, Montreal, Canada 4.Research Center of Adolescent Psychology and Behavior, School of Education, Guangzhou University, Guangzhou, China 5.School of Psychology, Nanjing Normal University, Nanjing, China
推荐引用方式 GB/T 7714	Huizhi Bai,Zhizi Liu,Ziqi Fu,,et al. Objective Metrics for Assessing Visual Complexity of Vehicle Dashboards: A Machine-Learning Based Study[J]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2023,14049:103-113.
APA	Huizhi Bai.,Zhizi Liu.,Ziqi Fu,.,Zihao Liu.,Huihui Zhang.,...&Liang Zhang.(2023).Objective Metrics for Assessing Visual Complexity of Vehicle Dashboards: A Machine-Learning Based Study.Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),14049,103-113.
MLA	Huizhi Bai,et al."Objective Metrics for Assessing Visual Complexity of Vehicle Dashboards: A Machine-Learning Based Study".Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14049(2023):103-113.