A Study of Icon Design Styles for Recognition in HUD Environments

Dihui Chu, Zhisheng Zhang, Fangzhou Dong, Wenyu Wu, Yunlong Tang

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

In field of AR research and icon design, a problem worthy of further discussion is whether the design style change will affect the user’s cognitive efficiency. With the development of intelligent automobile, the display of icons is no longer limited to the mobile phone and computer, but extends to the intelligent cockpits. The icon design style inside the human-computer interaction interface in automobile HMI and HUD directly relates to the driver’s cognitive performance and driving safety. Especially in the HUD, due to the vibration of the car itself, the display effect of the icon is significantly different from the traditional display interface. Therefore, the design style of the icon may have different effects on the driver’s cognition in different driving environments. In order to investigate this issue in depth, this paper designed a visual search task through simulation experiments to compare the effects of three different design styles of icons (linear icons, filled icons, and combined linear-filled Icon) on drivers’ recognition speeds in different vibration directions (horizontal and vertical) and at three vibration frequency levels (5 Hz, 10 Hz, and 15 Hz). The experimental results show that the linear design style icons display particularly well in the vibration environment, while in the vibration direction, the icons with transverse vibration are more recognizable compared to those with longitudinal vibration. These findings provide a reference for optimizing the design of icons in in-vehicle HUDs, which can help to improve drivers’ cognitive efficiency and driving safety.

Original languageEnglish
Title of host publication8th International Conference on Big Data and Internet of Things (BDIOT 2024)
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages26-32
Number of pages7
ISBN (Electronic)9798400717529
DOIs
Publication statusPublished - 2024
EventInternational Conference on Big Data and Internet of Things 2024 - Hybrid, Macao, China
Duration: 14 Sept 202416 Sept 2024
Conference number: 8th
https://dl.acm.org/doi/proceedings/10.1145/3697355 (Proceedings)

Conference

ConferenceInternational Conference on Big Data and Internet of Things 2024
Abbreviated titleBDIOT 2024
Country/TerritoryChina
CityMacao
Period14/09/2416/09/24
Internet address

Keywords

  • 3D UI design
  • Head-up Display
  • Human factors
  • vibration

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