Jin-Long Lin

Dr. Jin-Long Lin

College of Design, National Taipei University of Technology, Taipei, Taiwan
orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 August 2024 in Mathematics
Verified
Journal Article
Open access
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JLJin-Long Lin
Jin-Long Lin
MZMeng-Cong Zheng
Meng-Cong Zheng
Smart electric vehicles (SEVs) hold significant potential in alleviating the energy crisis and environmental pollution. The augmented reality (AR) dashboard, a key feature of SEVs, is attracting considerable attention due to its ability to enhance driving safety and user experience through real-time, intuitive driving information. This study innovatively integrates Kansei engineering, factor analysis, fuzzy systems theory, analytic hierarchy process, grey relational analysis, and factorial experimentation to evaluate AR dashboards’ visual imagery and subjective preferences. The findings reveal that designs featuring blue planar and unconventional-shaped dials exhibit the best performance in terms of visual imagery. Subsequent factorial experiments confirmed these results, showing that drivers most favor blue-dominant designs. Furthermore, in unconventional-shaped dial designs, the visual effect of vertical 3D is more popular with drivers than horizontal 3D, while the opposite is true in round dials. This study provides a scientific evaluation method for assessing the emotional experience of AR dashboard interfaces. Additionally, these findings will help reduce the subjectivity in interface design and enhance the overall competitiveness of SEV vehicles.

15 April 2025 in IEEE Access
Verified
Journal Article
Open access
JLJin-Long Lin
Jin-Long Lin
MZMeng-Cong Zheng
Meng-Cong Zheng
TWTao Wang
Tao Wang
PLPeng Liu
Peng Liu
With the continuous advancement of smart car and vehicle display technologies, liquid crystal display (LCD) dashboards have become the mainstream medium for displaying driving information. This makes the reading performance and user research of LCD vehicle dashboards critically important. In this study, we aim to evaluate the impact of the human-machine interface (HMI) design of vehicle LCD dashboards on driver readability and user experience. Twelve experts participated in a clustering experiment of vehicle dashboards, and 32 drivers participated in a simulated driving environment test of resident display information and temporary display information. The results for resident display information indicate that design type makes a significant difference in both reading performance and visual search efficiency. In addition, only the unconventional-shaped (L-shaped) dual-dial design achieves the "desired" outcome in the user experience evaluations. Regarding temporary display information, findings indicate that icons positioned at the top of the dashboard interface are more readable than those at the bottom. High prioritized or frequently used icons should be placed at the top of the screen. Alternatively, if icons must be positioned at the bottom, they should be no smaller than 8 mm in size. This research will help reduce the driver's visual workload and off-road sight time, reduce the risk of traffic accidents, and improve the driver's user experience.