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Abstract
The aim of this research is to develop a quantitative usability evaluation method (UEM) for elderly drivers, which has different weight values on each factor concerning physical and cognitive context of elderly drivers. An analysis of the relationship between universal design guidelines for elderly drivers and usability principles was conducted by using the quality function deployment method. In addition, developmental priorities are derived from analysis results of difficulty in achieving performance improvement, max relationship values, and relative weight. Furthermore, n and positive relationships among the universal design guidelines are defined by means of relationship analysis. Combining these results, a quantitative evaluation guideline for elderly drivers is derived, and based on the context and developmental goals of the developer, selective design is facilitated. The proposed UEM is compared with existing UEM in terms of thoroughness, validity, and effectiveness.
Additional information
Notes on contributors
In-Kyung Choi
In-Kyung Choi is a Ph.D. student in the Graduate School of Culture and Technology at KAIST, Korea. Her research interests include interaction design, usability evaluation, input modalities, universal accessibility, information visualization, and tangible user interface.
Won-Sup Kim
Won-Sup Kim is Associate Professor in the Department of Design at Seoul National University of Science and Technology, where he directs the Robot and Interaction Design Laboratory. He received his Ph.D. in Industrial Design from KAIST. His research interests include product design, car design, interaction design, UX, and universal design.
Dongman Lee
Dongman Lee is Professor in the Department of Computer Science and Engineering at KAIST, Korea. He received his Ph.D. in Computer Science and Engineering from KAIST. His research interests include pervasive computing, mobile computing, and Internet protocols.
Dong-Soo Kwon
Dong-Soo Kwon is Professor in the Department of Mechanical Engineering at KAIST, Korea. He received his Ph.D. in Mechanical Engineering from Georgia Institute of Technology. His research deals with human–robot interaction, medical robotics, telerobotics, and haptics.