Abstract: In-vehicle infotainment (IVI) features such as navigation assistance play an important role in the travel of drivers around the world. Frequent use of IVI, however, can easily increase the cognitive load of drivers, and its interface design, especially the quantity of icons when facing the driver's high frequency use of sub-functions (such as navigation, music, phone call) under the driving situation, has not been fully researched. To optimize the number of icons, this study conducted a systematic evaluation of the IVI human machine interface (HMI) using single-factor and multivariate comprehensive influence analysis. One-way ANOVA results showed that the 3-icon design scored relatively well in subjective driver assessment, and the 4-icon design was best in vehicle index. The fuzzy synthetic evaluation results showed that 3-icons had the highest overall score. This study is the first to use the fuzzy synthetic evaluation method to assess the HMI design of IVI. The results of this study can provide support for optimizing icon quantity and for use of this method for the other HMI features design of IVI.
Jiawen Chen, Xuesong Wang*, Zhouyang Cheng, Yan Gao. HMI Evaluation of In-Vehicle Infotainment Icon Quantity: A Fuzzy Synthetic Evaluation Model Based on A Driving Simulator. Transportation Research Board 101st Annual Meeting, Washington D.C., USA, 2022. 1.9-13.