Automotive cluster UI design based on time and path from the perspective of the 'Passenger'

Abstract

Background One important design issue is the examination of how the user interface (UI) supports the new user role in future mobility. However, there are few design studies on the passenger's cognitive needs and behavior in autonomous vehicles (AVs) based on empirical data. There is no doubt that autonomous mobility technologies are growing. The technology is already aiding the driving experience, and it will change the mobility culture and the transition of 'driver' into 'passenger.' This study is based on the premise that future AVs are capable of performing all driving tasks and proposes a set of passenger-centered automotive cluster UI designs for future mobility employing two factors: time and path. A collection of empirical data is provided to understand the passenger's perspective. Methods In this study, a solid set of empirical data on the cognitive needs of passengers is collected. Human cognitive characteristics and driving tasks are investigated from various viewpoints to understand the passenger's perspective. The cognitive relationship in the driving environment is analyzed through a literature review on situation awareness (SA) and structuring of the data flow framework. The framework is further explored by connecting the technological role transformation to the passenger. Three sets of user tests and in-depth interviews were undertaken to construct the empirical database on the passenger. The user tests were designed employing the Wizard of Oz method, and the results were summarized using descriptive and exploratory analysis. Based on these insights, a set of UI designs from the perspective of the passenger was proposed, and usability tests were conducted to verify its effectiveness and usability. Results The results of the tests demonstrate that a major percentage of the information request was related to time (current time and duration) and path (vehicle location and surroundings). Based on the data, a UI framework was built. Two usage scenarios were designed, time-full and time-less, for better in-situation comprehension. Time- and route-based UI were proposed to flow with the scenarios. A usability test was conducted, and a passenger's cognitive framework was defined. There are two aspects to this study: the data flow frameworks of the driver/passenger, and the UI design proposal for the future AVs. The detailed data relationship between the user, the vehicle, and the road is determined as a framework. Also, the driver's data perceiving flow is analyzed to understand the data flow change due to AVs. Furthermore, the cognitive framework of the passenger was proposed based on the data. Conclusions This study provides a solid understanding of drivers' emerging needs when they are relieved of the cognitive burden of driving tasks. The UI features for AVs are introduced based on the empirical data and research related to the provision of better situation awareness, focusing on time and location. This study contributes to the extant literature by observing the perspective of passengers in autonomous vehicles based on a qualitative study. The proposed UI design will be further explored as a communication method between the system and the passive user in future mobility.