Biblio

The automotive domain currently experiences a radical transition towards automation, connectivity and digitalization. This is a cause for major change in human-machine interaction. The research presented here examines 1) company visions of future mobility 2) user's reaction to the first trials of these visions. The data analyses reveal that implementing companies' visions for 2040 requires improvement concerning user acceptance. One way of improving user acceptance is to integrate emotion recognition in manual and automated vehicles. By reacting to users' positive and negative emotions, vehicles can learn to improve driving behavior, communication and to adjust driver assistance accordingly. Therefore, a roadmap for future research in emotion recognition has been developed by interviews with twelve experts in the field. Emotions that they judged to be most relevant to detect include anger, stress and fear, amongst others. Furthermore, ideas on sensors for emotion recognition, potential countermeasures for the negative effects of emotions and additional challenges were collected. The research presented is designed to shape further research directions of in-car emotion recognition.