@inproceedings{hwang2026adaptivecartouchscreen,
  title = {A Framework for Adapting In-Car Touchscreen Interfaces to Driver Behaviors, Perception, and Cognition},
  author = {Hwang, Seokhyun and Shen, Xiyuan and Filipowicz, Alexandre L. S. and Best, Andrew and Costa, Jean and Carter, Scott and Fogarty, James and Wobbrock, Jacob O.},
  booktitle = {Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems},
  year = {2026},
  pages = {1-23},
  doi = {10.1145/3772318.3790434},
  url = {https://doi.org/10.1145/3772318.3790434},
  abstract = {Although in-car touchscreens expand interaction possibilities, they risk compromising driver safety and vigilance. We propose a data- and expert-informed framework for designing adaptive touchscreens that respond to a driver’s usage profile and cognitive state, maximizing usability while mitigating safety risks. First, in a driving simulator study, we find that cognitive load slows touchscreen button selections by 20\% and produced shorter, more frequent off-road glances. We also find that enlarging buttons improves selection speeds by 0.3 seconds but at the cost of requiring more display pages. Next, these findings informed a co-design session with expert in-cabin designers, generating guidelines for adaptive interfaces that balance usability and safety. These guidelines form the basis of our Profile-State Adaptive (PSA) framework, which integrates driver profiles with cognitive states to guide interface adaptations. We then extend the framework to include a quantitative Time-Cost model as well as design patterns for adaptive layouts across usage profiles and cognitive demands.},
  keywords = {Cognition, Human-AI Interaction, Automotive, Conference, FA}
}