Analysis of Effects of Interaction Modes on IVIS Based on Sensory Information Recognition

The design of in-vehicle information system (IVIS) has become the core of autobiles' human-machine interaction interface. From touching screen interaction to voice or gesture recognition, the influence of different interaction modes is an important research field. Based on the principle of Kansei Engineering, the study collected data of a large sample and conducted factor analysis for these interaction modes. The aim is to find out potential factors behind them and identify the representative interaction modes by the size of factor loadings. By means of multiple regression equation, the representative modes' influence on driving experience and the significance level are clarified.