Development of empathic autonomous vehicles through understanding the passenger’s emotional state

Abstract

Emotion recognition is crucial to increase user acceptance in autonomous driving. SUaaVE project aims to formulate ALFRED, defined as the human-centered artificial intelligence to humanize the vehicle actions by estimating the emotions felt by the passengers and managing preventive or corrective actions, providing tailored support. This paper presents the development of an emotional model able to estimate the values of valence (how negative or positive a stimulus is) and arousal (the level of excitement) from the analysis of physiological signals. The model has been validated with an experimental test simulating different driving scenarios of autonomous vehicles. The results found that driving mode can influence the emotional state felt by the passengers. Further exploration of this emotional model is therefore advised to detect on board experiences and to lead to new applications in the framework of empathic vehicles.

Keywords: Autonomous vehicles, Empathic vehicles, Human-centered artificial intelligence, Emotional model, Physiological Signals

DOI: 10.54941/ahfe1002436