Enhancing In-Vehicle Driving Assistance Information Under Connected Vehicle Environment

Abstract

As users’ needs are changing and new technologies are developing at a faster rate than ever before, it is important to evaluate and update the design and mechanism of specific products based on various points and factors. This paper assessed the effectiveness of in-vehicle warning and assistance information design under reduced visibility driving conditions using the Kansei engineering methods. Various warning and assistance information design scenarios through in-vehicle head-up display (HUD) under the connected vehicle environments were collected and devised for the analysis. In order to determine the connection between the information features and design elements and the desired emotional needs of drivers in low visibility conditions, the Kansei engineering quantification Type I theory with two-level hierarchy structure and the partial least square-based Kansei engineering approaches were utilized. By analyzing the emotion dimensions and design category factors, the optimized in-vehicle HUD information designs were identified for different driver groups (i.e., all, male, and female participants) based on three driving scenarios considering changes of weather, real-time crash risk, and traffic conditions. On the basis of understanding the importance of collecting drivers’ needs and perceptions for different combinations of information technologies, the optimized information features and design elements could be appreciated.