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Detail
Conference Paper
Design of Automotive Digital Instrument Cluster Adjustable to Driver’s Cognitive Characteristics
- 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
- Language
- English
- Type
- Conference Paper
- Project Code
- 19ZS1300, The development of smart context-awareness foundation technique for major industry acceleration, Kim Do Hyun
- 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, Effective interaction, Instrument cluster, Novice drivers, User interface, elderly drivers, interaction methods, user experience, work environment