Motivated by the lack of a comprehensive framework for passenger comfort in highly AVs , this workshop brings together researchers and practitioners from the AutomotiveUI community to develop a holistic perspective on comfort in automated driving. Previous work has examined individual factors in isolation, while these dimensions require a holistic approach. The workshop therefore aims to identify key comfort determinants, explore their interdependencies, and develop a shared research agenda and conceptual model for passenger comfort in automated vehicles.
Sessions
- Session 1: Setting the stage
After a short round of introductions, the workshop will begin with an interactive brainstorming session. Participants are first asked to individually reflect on the central question: “What makes passengers feel comfortable in an (L4–L5) automated vehicle?” Each participant silently writes down factors, examples, concerns, and research questions related to comfort. These ideas are then shared and collaboratively clustered into higher-level themes. Through facilitated discussion, the emerging clusters are organized into overarching categories, which are expected to include 1. vehicle dynamics, 2. driving style, and 3. in-vehicle HMI (but may also reveal additional dimensions such as trust, personalization, situational context, user characteristics, or environmental factors). - Session 2: Digging deeper
Building on the 3+ clusters identified, participants divide into parallel working groups (or a World Café format) organized around the core dimensions that emerged from the literature (and/or the braingstorming): 1. Vehicle dynamics, 2. (automated) driving style, in-vehicle HMI, etc. Each group is tasked with identifying the most important variables, design parameters, and open research challenges within its respective dimension. For example, the vehicle dynamics group focuses on aspects such as acceleration, braking behavior, jerk, speed adaptation, and motion sickness; the driving style group investigates topics including safety margins, lane-changing behavior, contextual adaptation, and personalized driving preferences; the HMI group explores transparency, explainability, information presentation, trust calibration, and entertainment functions. Each group develops a structured overview of comfort-relevant factors and their assumed influence on the passenger experience. - Session 3: Linking the dimensions
In the subsequent plenary session, the focus shifts to the interaction between dimensions. All groups briefly present their findings and jointly discuss how they influence each other. Particular attention is paid to identifying dependencies and trade-offs, and context-specific comfort challenges that are unique to L4–L5 automated vehicles. The goal of this session is to establish connections between isolated research perspectives and to synthesize them into a shared framework for passenger comfort in highly automated vehicles. - Session 4: Challenges and opportunities
The final part of the workshop is dedicated to the collaborative discussion of an integrated comfort framework. Participants synthesize the identified factors and interactions into a conceptual model that captures the relationship between the core dimensions with contextual factors and user characteristics. The workshop concludes with an identification of key research gaps, methodological challenges, context-specific comfort issues, and opportunities for future collaboration.
Expected Outcome
The workshop is expected to generate a shared understanding of passenger comfort in highly automated vehicles by identifying and structuring the key factors that influence the user experience. By integrating previously separate perspectives, such as vehicle dynamics, automated driving style, HMI, trust, motion sickness, and NDRTs, participants will develop an initial understanding of the interaction between relevant core dimensions, such as vehicle dynamics, driving style, and in-vehicle HMIs, that eventually shall lead to a shared framework for L4—L5 passenger comfort. The framework should comprise a taxonomy of influencing factors, prioritized research questions, methodological recommendations, and concrete directions for follow-up AutomotiveUI research and collaborations.