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Computational Models for In-Vehicle User Interface Design: A Systematic Literature Review, , , , and . Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 204–215. New York, NY, USA, Association for Computing Machinery, (Sep 22, 2024)Changing Lanes Toward Open Science: Openness and Transparency in Automotive User Research, , , , , , , , and . (July 2024)ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces, , , and . Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, New York, NY, USA, Association for Computing Machinery, (2022)Automotive UX design and data-driven development: Narrowing the gap to support practitioners, , , , , and . Transportation Research Interdisciplinary Perspectives, (2021)It Is Not Always Just One Road User: Workshop on Multi-Agent Automotive Research, , , , and . Adjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 268–272. New York, NY, USA, Association for Computing Machinery, (Sep 22, 2024)Destination Prediction Based on Partial Trajectory Data, , , and . (2020)Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces, , , and . Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 81--92. (2023)Breaking Barriers: Workshop on Open Data Practices in AutoUI Research, , , , , , , and . Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 227--230. (2023)The Role and Potentials of Field User Interaction Data in the Automotive UX Development Lifecycle: An Industry Perspective, , and . 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 141–150. New York, NY, USA, Association for Computing Machinery, (2020)Explaining the Unexplainable: The Impact of Misleading Explanations on Trust in Unreliable Predictions for Hardly Assessable Tasks, , , and . Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, page 36–46. New York, NY, USA, Association for Computing Machinery, (2024)