Automated driving is expected to bring several benefits such as improved traffic safety, reduced congestions and emissions, social inclusion, enhanced accessibility and higher driving comfort. A central human–machine interaction issue addresses the question of how automated vehicles should drive to ensure comfort and a positive driving experience. The project KomfoPilot aimed at investigating, assessing and enhancing comfort during automated driving by two driving simulator studies and a test track study. Sensors such as wearable devices, eye tracking, face tracking and motion tracking allowed for the integration of driver state data with information about the vehicle and the surroundings. Various driving styles as well as display solutions were evaluated for reducing discomfort. In addition, privacy issues were continuously monitored for all aspects over the project lifetime. Section 2.1 gives an overview on the background and aims of the project, definitions of central concepts and an overall summary of key results. Methodological details on the experimental design, participants, assessment of discomfort, sensors and questionnaires of the three studies are presented in Sect. 2.2. A first research objective was to find factors that affect comfort on a rather general level, such as driving situations and driving style parameters (e.g. speed, longitudinal/lateral distance, driving style familiarity). These results are presented in Sects. 2.3 and 2.4. A second objective was the development of algorithmic approaches for real-time discomfort detection based on sensor data. Results on physiological discomfort indicators are presented in Sect. 2.5, whereas Sect. 2.6 gives an overview of the work on algorithms. Privacy and liability aspects are discussed in Sect. 2.7.