Abstract
Automated vehicles (AVs) are expected to transform the passenger experience, which is largely shaped by the emotions perceived on board. This study, conducted as part of the SUaaVE H2020 project, aimed to identify key emotions and generate associated driving scenarios, focusing on vehicles with high levels of automation. Using the Orthony Claire Collins model (OCC model), 45 participants from Spain and Italy, through an online bulletin board, described situations that could trigger emotional responses as passengers in AVs. A qualitative analysis led to the development of a scenario database featuring 15 key situations, each capable of evoking different emotions. The results reveal that “satisfaction” and “joy” were the most prominent positive emotions, while “fear” emerged as the most frequently mentioned negative emotion. These findings offer valuable insights to guide the design and optimization of AVs to improve passenger experience and emotional well-being.
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Acknowledgements
This work was funded by the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No. 814999.
This activity has been developed in the framework of the MEDUSA project. MEDUSA is a Technological Network of engineering applied to the development of intelligent solutions for automated mobility using a human-centred approach (CER-20231011), Red de Excelencia CERVERA founded by the Ministerio de Ciencia, Innovación y Universidades through the Centro para el Desarrollo Tecnológico y la Innovación E.P.E. (CDTI), using the funding of The Recovery and Resilience Facility (NextGenEU) from the European Union.
The knowledge shown in this paper will be used an input for BERTHA Horizon Europe project (Grant Agreement No. 101076360).
The authors would like to thank Centro Ricerche Fiat (CRF) for the survey conducted in Italy.
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Palomares, N. et al. (2025). Definition of Relevant Scenarios in Automated Vehicles Times Study the Emotional State of the Passengers. In: Plácido da Silva, H., Cipresso, P. (eds) Computer-Human Interaction Research and Applications. CHIRA 2024. Communications in Computer and Information Science, vol 2371. Springer, Cham. https://doi.org/10.1007/978-3-031-83845-3_32
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