Improving Passenger Experience and Trust in Automated Vehicles Through User-Adaptive HMIs: “The More the Better” Does Not Apply to Everyone

Abstract

Automated vehicles promise transformational benefits for future mobility systems, but only if they will be used regularly. However, due to the associated loss of control and fundamental change of in-vehicle user experience (shifting from active driver to passive passenger experience), many humans have reservations toward driving automation, which question their sufficient usage and market penetration. These reservations vary based on individual characteristics such as initial attitudes. User-adaptive in-vehicle Human-Machine Interfaces (HMIs) meeting varying user requirements may represent an important component of higher-level automated vehicles providing a pleasant and trustworthy passenger experience despite these barriers. In a driving simulator study, we evaluated the effects of two HMI versions (with permanent vs. context-adaptive information availability) on the passenger experience (perceived safety, understanding of driving behavior, driving comfort, driving enjoyment) and trust in automated vehicles of 50 first-time users with varying initial trust (lower vs. higher trust group). Additionally, we compared the user experience of both HMIs. Presenting driving-related information via HMI during driving improved all assessed aspects of passenger experience and trust. The higher trust group experienced automated driving as safest, most understandable and most comfortable with the context-adaptive HMI, while the lower trust group tended to experience the highest safety, understanding and comfort with the permanent HMI. Both HMIs received positive user experience ratings. The context-adaptive HMI received generally more positive ratings, even though this preference was more pronounced for the higher trust group. The results demonstrate the potential of increasing the system transparency of higher-level automated vehicles through HMIs to enhance users’ passenger experience and trust. They also consolidate previous findings on varying user requirements based on individual characteristics. User group-specific HMI effects on passenger experience support the relevance of user-adaptive HMI concepts addressing varying needs of different users by customizing HMI features, such as information availability. Consequently, providing full information permanently cannot be recommended as a universal standard for HMIs in automated vehicles. These insights represent next steps toward a pleasant and trustworthy passenger experience in higher-level automated vehicles for everyone, and support their market acceptance and thus the realization of their expected benefits for future mobility and society.

What’s on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while Driving

“…We mimic the driver's interaction with the vehicle's interface while driving through the auditory n-back task and the visual search task, which are equivalent to a speech-based and a touch-based interaction respectively. While our work focuses on this general dual task approach of manipulating an interface while driving, it is also applicable to more specific applications such as transfer-of-control scenarios for automated and semi-automated vehicles [79]; simplified interfaces, or personalized warnings for mentally exhausting situations [88]; and increasing the user's trust through system awareness and transparency [44]. Thus, an adaptive personalized interface observant of the driver's mental capacities can be implemented.…”

Cross-Cultural Expectations from Self-Driving Cars

“…One method of cultivating trust for self-driving cars is to improve on human-machine interaction, by designing self-driving cars in a way that communicates to passengers and have them play a more active role in the experience one can deliver a more trustful system for users. This is supported by research conducted by Hartwich et al where evidence suggests that even given a SAE Level 4-5 system where no human interaction is required, the introduction of monitoring tools significantly improves passenger trust 6 . Further research conducted by Hartwich et al shows that the significance of the first experience with self-driving cars greatly impacts the trust one associates with the technology 7 .…”

Meeting User Needs in Vehicle Automation

“…To reduce such subjective uncertainties in the use of AVs or automated systems in general, these systems must focus on the users and their needs. For instance, recent studies point to the relevance of considering the information needs of users of AVs (Hartwich et al, 2021). To relate the needs of users and the design of AVs, we developed the approach of user-focused automation.…”

“…Group-specific effects of iHMIs with differing information availability on passenger experience and trust (Hartwich et al, 2021;Hollander et al, 2021).…”