Towards a Conceptual Model of Users’ Expectations of an Autonomous In-Vehicle Multimodal Experience

Ince, Ecem Berfin; Cha, Kyungjoo; Cho, Junghyun · 2024 · Crossref

DOI: 10.1155/2024/7418597

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Summary

This study addresses the lack of holistic understanding regarding user expectations for multimodal interactions in autonomous vehicles (AVs). While previous research has primarily evaluated specific multimodal prototypes or technical integrations, this paper aims to identify the critical aspects that characterize the overall in-vehicle multimodal experience. The research question focuses on determining what users expect from these interactions to inform early-stage design processes. To answer this, the authors employed a qualitative research design consisting of two linked studies. Study 1 involved an online survey of 150 participants to establish a taxonomy of six in-vehicle user contexts where intuitive interaction is critical, such as "switching-required" or "emotion-underlain" contexts. Study 2 utilized five design fiction workshops with 17 participants, specifically recruited from the fiction and science-fiction writing communities to enhance creative engagement with future scenarios. Participants engaged in brainstorming, sci-fi scenario writing, and roleplaying within assigned contexts. The resulting data, including transcriptions and fictional narratives, underwent thematic analysis following established guidelines. Three reviewers conducted an inter-rater reliability check to ensure coding consistency. The analysis extracted 22 subthemes representing users’ expected tasks and interactions. The researchers identified two primary dimensions that critically impact these expectations: attention and duration. These dimensions were selected because they achieved a 100% inter-rater reliability rate, whereas other potential themes like proactivity or control showed lower reliability scores. The study found that user expectations vary along a spectrum of attention (low to high) and duration (short to long). Based on these findings, the authors propose a conceptual model featuring a two-dimensional spectrum that defines four distinct layers of multimodal experience: sustained, distinct, concurrent, and coherent. The significance of this work lies in providing a holistic framework for designers to understand user expectations beyond specific device evaluations. By categorizing interactions through the lenses of attention and duration, the model offers a structured approach for designing informed multimodal experiences in future AVs. This allows designers to make better decisions during the initial stages of development, ensuring that in-vehicle interactions align with the diverse contextual needs and preferences of occupants.

Key finding

Attention and duration are the two critical dimensions that characterize and differentiate users' expectations of in-vehicle multimodal experiences in autonomous vehicles.

Methodology

survey

Sample size: 17

Provenance

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Topics

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• automation
• mode awareness
• automation surprise
• situational awareness
• generative ai voice assistants
• voice interaction

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: design guidelines
• Empirical Findings: self report data
• Theoretical Contribution: conceptual framework