Perceived Visual Complexity of In-Vehicle Information Display and Its Effects on Glance Behavior and Preferences

Seul Chan Lee, Hwan Hwangbo, Yong Gu Ji

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


Despite enhancements in the visual complexity of in-vehicle information display in recent years, few studies have examined the effects of such increased complexity. We conducted this study with the following objectives: (1) to suggest a framework for predicting the perceived visual complexity (PVC) of in-vehicle information display; (2) to examine the effects of PVC on the visual behavior of human operators; (3) to investigate the relationship between preferences and PVC. A theoretical framework to evaluate PVC was developed, and a survey study was used to collect participants’ perceptions on visual complexity. A regression analysis was employed to find the relationship between each of three factors and PVC. Two of the factors—quantity and variety—showed a positive correlation with PVC, whereas the third factor, relation, exhibited a negative correlation. Visual search experiments were conducted to test the effects of PVC on the performance of visual search tasks and glance behavior. The results showed that the high level of PVC leads to more time-on-task and number of fixations. We also found that preference for in-vehicle information displays was inversely proportional to PVC. The results enable us to predict how human operators perceive visual complexity and explain the influence of PVC on human behavior.

Original languageEnglish
Pages (from-to)654-664
Number of pages11
JournalInternational Journal of Human-Computer Interaction
Issue number8
Publication statusPublished - 2016 Aug 2

Bibliographical note

Funding Information:
This work was supported by Mid-Career Researcher Program through NRF grant funded by the MSIP (Ministry of Science, ICT, and Future Planning) (grant number NRF-2013R1A2A2A03014150).

Publisher Copyright:
© 2016 Taylor & Francis Group, LLC.

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications


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