Titlebook: HCI in Mobility, Transport, and Automotive Systems; 5th International Co Heidi Krömker Conference proceedings 2023 The Editor(s) (if applic

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FIGCONs: Exploiting FIne-Grained CONstructs of Facial Expressions for Efficient and Accurate Estimats high accuracy and less cost for deploying redundant sensors/cameras inside the vehicle. However, existing approaches for in-vehicle ML-based predictors heavily rely on the raw driver data for processing, which mcan push the burdens on multiple components, ranging from on-vehicle devices to Interne

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Design Study on the Effect of Intelligent Vehicles Interaction Mode on Drivers’ Cognitive Load order to improve the driving experience of this group and prevent traffic accidents as much as possible. The Multiple-Resource Theory is used to analyze the interaction modes of intelligent vehicles in this study, and the role of Physical Stuff interaction, Touch-screen Interaction, Voice Interacti

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Consistency Analysis of Driving Style Classification Based on Subjective Evaluation and Objective Dricipants participated in the study and completed the MDSI-C questionnaire and drove in a simulator for 50 min, which involved seven different types of driving scenarios on a highway. The data obtained from the questionnaire scores on six dimensions and thirteen driving behavior data were used to per

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Do Drivers Vary in Preferences for Automated Driving Styles Across Different Scenarios? Evidence froechnology. In order to enhance this experience, it is necessary to understand drivers’ preferences and attitudes towards the automated driving style. In this study, 32 drivers with 4 manual driving styles were recruited for simulation experiment under 2 driving scenarios. During each scenario, the d

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