User-Centered Challenges and Strategic Opportunities in Automotive UX: A Mixed-Methods Analysis of User-Generated Content

Abstract

Featured Application: The findings of this article may be utilized within the automotive industry to systematically validate existing User Interface (UI)/User Experience (UX) concepts based on the derived implications from user-reported challenges, and to inform the development of novel UI/UX concepts guided by the proposed framework and design recommendations. With the ongoing integration of advanced technologies into modern vehicle systems, understanding user interaction becomes a critical factor for safe and intuitive operation—especially in the transition towards autonomous driving. This article uncovers user-reported challenges of UX and in-vehicle UIs. The analysis is based on quantitative and qualitative evaluations of user-generated content (UGC) from automotive-focused online forums. The quantitative analysis is conducted by Natural Language Processing (NLP), while qualitative evaluation is performed through Mayring, applying a deductive–inductive category formation approach. The study investigates challenges related to interface complexity, driver distraction, and missing user diversity in the context of increasing digitalization. Based on the analysis, a set of practical design implications is presented, emphasizing context-sensitive function reduction, multimodal interface concepts, and UX strategies for reducing complexity. It has become evident that UX concepts in the automotive context can only succeed if they are adaptive, safety-oriented, and tailored to the needs of heterogeneous user groups. This leads to the development of an interaction strategy model, serving as a transitional framework for guiding the shift from manual to fully automated driving scenarios. The paper concludes with an outlook on further research to validate and refine the implications and UX framework.