One critical factor of success and user acceptance in connected automated vehicles (CAVs) is trust in technology, being the main obstacle that remains from a customer’s perspective. Trust in automated systems is based on feelings of safety and acceptance, being the emotional process the most influential aspect. One of the main ambitions of SUaaVE project (SUpporting acceptance of automated VEhicle) is to develop an emotional model to understand the passenger’s state during the trip (in Real-Time), based on body biometrics, allowing to adapt the vehicle features to enhance the in-vehicle user experience, while increasing trust, and therefore acceptance. This research addressed a initial experiments to identify changes in the emotional state of the occupants in different driving experiences (in a driving simulator and in real conditions) by measuring and analysing the physiological signals of the participants, serving as a basis for the generation of the emotional model. The results showed that it is possible to estimate the level of Arousal and Valence of the participants during the journey from the analysis of ECG, EMG and GSR signals. These results have positive implications for the automobile industry facilitating a better integration of human factor in the deployment of CAV.