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Conference Paper Design of Automotive Digital Instrument Cluster Adjustable to Driver’s Cognitive Characteristics
Cited 4 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Young-Jin Kwon, Jin-Kyu Choi, Juil Jeon, Kyongho Kim, Byungtae Jang
Issue Date
2019-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.461-463
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939993
Abstract
In this paper, we propose an adjustable digital instrument cluster designed to provide an effective user interface and user experience (UI/UX) depending on the driver's age, gender, personal driving experience, and driver's emotions and conditions changes in driving. To make this possible, firstly we build a theme structure that can link with scripts to reconfigure flexibly the predetermined digital instrument cluster according to various situations that occur during driving, such as elderly drivers, female drivers, novice drivers, and general drivers. Secondly, we defined objects and elements to provide a digital instrument cluster that can change dynamically according to the script that makes up the cluster, and this library designed provides a work environment for users to personalize some themes. In addition, the proposed system can basic research to derive effective interaction methods by providing an environment suitable for evaluating the usefulness of each driver groups.
KSP Keywords
Basic research, Cognitive characteristics, Driving experience, Instrument cluster, Interaction methods, Novice drivers, User experience, User interface(UI), effective interaction, elderly drivers, work environment