Assessment model for perceived visual complexity of automotive instrument cluster

Sol Hee Yoon; Jihyoun Lim; Yong Gu Ji

doi:10.1016/j.apergo.2014.07.005

Assessment model for perceived visual complexity of automotive instrument cluster

Sol Hee Yoon, Jihyoun Lim, Yong Gu Ji

Dept. of Safety Engineering

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

This research proposes an assessment model for quantifying the perceived visual complexity (PVC) of an in-vehicle instrument cluster. An initial study was conducted to investigate the possibility of evaluating the PVC of an in-vehicle instrument cluster by estimating and analyzing the complexity of its individual components. However, this approach was only partially successful, because it did not take into account the combination of the different components with random levels of complexity to form one visual display. Therefore, a second study was conducted focusing on the effect of combining the different components. The results from the overall research enabled us to suggest a basis for quantifying the PVC of an in-vehicle instrument cluster based both on the PVCs of its components and on the integration effect.

Original language	English
Pages (from-to)	76-83
Number of pages	8
Journal	Applied Ergonomics
Volume	46
Issue number	Part A
DOIs	https://doi.org/10.1016/j.apergo.2014.07.005
State	Published - 1 Jan 2015

Keywords

Assessment model
Perceived visual complexity
Quantifiable measurement variables

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10.1016/j.apergo.2014.07.005

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title = "Assessment model for perceived visual complexity of automotive instrument cluster",

abstract = "This research proposes an assessment model for quantifying the perceived visual complexity (PVC) of an in-vehicle instrument cluster. An initial study was conducted to investigate the possibility of evaluating the PVC of an in-vehicle instrument cluster by estimating and analyzing the complexity of its individual components. However, this approach was only partially successful, because it did not take into account the combination of the different components with random levels of complexity to form one visual display. Therefore, a second study was conducted focusing on the effect of combining the different components. The results from the overall research enabled us to suggest a basis for quantifying the PVC of an in-vehicle instrument cluster based both on the PVCs of its components and on the integration effect.",

keywords = "Assessment model, Perceived visual complexity, Quantifiable measurement variables",

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AU - Lim, Jihyoun

AU - Ji, Yong Gu

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N2 - This research proposes an assessment model for quantifying the perceived visual complexity (PVC) of an in-vehicle instrument cluster. An initial study was conducted to investigate the possibility of evaluating the PVC of an in-vehicle instrument cluster by estimating and analyzing the complexity of its individual components. However, this approach was only partially successful, because it did not take into account the combination of the different components with random levels of complexity to form one visual display. Therefore, a second study was conducted focusing on the effect of combining the different components. The results from the overall research enabled us to suggest a basis for quantifying the PVC of an in-vehicle instrument cluster based both on the PVCs of its components and on the integration effect.

AB - This research proposes an assessment model for quantifying the perceived visual complexity (PVC) of an in-vehicle instrument cluster. An initial study was conducted to investigate the possibility of evaluating the PVC of an in-vehicle instrument cluster by estimating and analyzing the complexity of its individual components. However, this approach was only partially successful, because it did not take into account the combination of the different components with random levels of complexity to form one visual display. Therefore, a second study was conducted focusing on the effect of combining the different components. The results from the overall research enabled us to suggest a basis for quantifying the PVC of an in-vehicle instrument cluster based both on the PVCs of its components and on the integration effect.

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KW - Quantifiable measurement variables

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Assessment model for perceived visual complexity of automotive instrument cluster

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Keywords

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