Publication
In-Vehicle Interface Adaptation to Environment-Induced Cognitive Workload
Elena Meiser; Alexandra Katrin Alles; Samuel Selter; Marco Molz; Amr Gomaa; Guillermo Reyes
In: AutomotiveUI'22 Adjunct: International Conference on Automotive User Interfaces and Interactive Vehicular Applications. International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI-2022), located at 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 17-20, Seoul, Korea, Republic of, ISBN 978-1-4503-9428-4, Association for Computing Machinery (ACM), 9/2022.
Abstract
Many car accidents are caused by human distractions, including cognitive distractions. In-vehicle human-machine interfaces (HMIs) have evolved throughout the years, providing more and more functions. Interaction with the HMIs can, however, also lead to further distractions and, as a consequence, accidents. To tackle this problem, we propose using adaptive HMIs that change according to the mental workload of the driver. In this work, we present the current status as well as preliminary results of a user study using naturalistic secondary tasks while driving (i.e., the primary task) that attempt to understand the effects of one such interface.
Projects
- CAMELOT - Continuous Adaptive Machine-Learning of Transfer of Control Situations
- SC_APX-HMI - An Adaptive and Personalized in-Vehicle Machine-User-Inerface for an Improved User Experience