Citation

Palomares N, Mateo B, Belda-Lois JM, Iranzo S, Silva J, de Nalda-Tárrega V, Laparra-Hernández J, Solaz JS. Transp. Res. Proc. 2023; 72: 3917-3924.

Copyright

(Copyright © 2023, Elsevier Publications)

DOI

10.1016/j.trpro.2023.11.489

PMID

unavailable

Abstract

Emotion Recognition is an emerging area in the field of automotive research focused on improving the driving experience and driver behavior. In the framework of automated vehicles, it is vitally important to detect and understand the emotional state of occupants in order to provide them with tailored support and to develop corrective actions to increase their acceptance of such vehicles. The H2020 SUaaVE project aims to develop an emotional model able to estimate passenger state through the analysis of their physiological signals. 50 drivers have experienced different automated driving scenarios with our HAV driving simulator, gathering their biometric measurements and behavior. The application of the emotional model shows significant differences in the emotion experienced by the participants in terms of valence and arousal across the different simulated scenarios.

Language: en

Keywords

automated vehicles; Emotion recognition; empathic vehicles; physiological signals