Optimizing Human-machine Interface Design through Information Transparency in Autonomous Driving Systems

Abstract

With the development of autonomous driving technology, emerging functions and various services in vehicles are proliferating, and the information that drivers need to operate and master is also gradually increasing. The complexity of vehicle interaction information leads to the problem of difficult to understand and lack of trust in the in-vehicle human-machine interface (HMI). Transparency of the in-vehicle HMI refers to the extent to which users can access and understand the information and data in the vehicle operation and decision-making process. It not only enhances the mechanism of effective interaction between the driver and the in-vehicle HMI, but also serves as an important indicator for establishing the driver's trust in the self-driving vehicle. Therefore, this study firstly collated theoretical models related to information transparency. Afterwards, the information transparency levels were further analysed and sorted out through behavioural analysis experiments and interview evaluations. Finally, an information transparency hierarchy model for in-vehicle human-machine interface (HMI) is constructed, aiming to form an information transparency design standard for in-vehicle HMI. The model is used as a basis for design practice. The information transparency hierarchy model proposed in this study can effectively guide the design of information type and hierarchy of in-vehicle human-machine interface, significantly improve the driver's understanding of the vehicle system and the degree of trust, and provide a reliable solution to enhance the user's ability to grasp the vehicle's driving system, as well as provide a new methodology and ideas for the research of information transparency in the field of self-driving cars.

Keywords: Information transparency, Trust level, User experience, Availability, Human-machine interface

DOI: 10.54941/ahfe1005427