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http://dx.doi.org/10.5143/JESK.2015.34.3.235

Developing Visual Complexity Metrics for Automotive Human-Machine Interfaces  

Kim, Ji Man (Department of Information and Industrial Engineering, Yonsei University)
Hwangbo, Hwan (Department of Information and Industrial Engineering, Yonsei University)
Ji, Yong Gu (Department of Information and Industrial Engineering, Yonsei University)
Publication Information
Journal of the Ergonomics Society of Korea / v.34, no.3, 2015 , pp. 235-245 More about this Journal
Abstract
Objective: The purpose of this study is to develop visual complexity metrics based on theoretical bases. Background: With the development of IT technologies, drivers process a large amount of information caused by automotive human-machine interface (HMI), such as a cluster, a head-up display, and a center-fascia. In other words, these systems are becoming more complex and dynamic than traditional driving systems. Especially, these changes can lead to the increase of visual demands. Thus, a concept and tool is required to evaluate the complicated systems. Method: We reviewed prior studies in order to analyze the visual complexity. Based on complexity studies and human perceptual characteristics, the dimensions characterizing the visual complexity were determined and defined. Results: Based on a framework and complexity dimensions, a set of metrics for quantifying the visual complexity was developed. Conclusion: We suggest metrics in terms of perceived visual complexity that can evaluate the in-vehicle displays. Application: This study can provide the theoretical bases in order to evaluate complicated systems. In addition, it can quantitatively measure the visual complexity of In-vehicle information system and be helpful to design in terms of preventing risks, such as human error and distraction.
Keywords
In-vehicle Information system (IVIS); Perceived Visual Complexity (PVC); Human visual perception; Human-machine Interface; Instrument cluster;
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