Towards understanding emotional reactions of driver-passenger dyads in automated driving

Published in Proceedings of the 13th IEEE International Conference on Automatic Face & Gesture Recognition, IEEE 2018

Abstract

Automated driving has the potential to reduce the amount of fatal crashes, lighten the burden of commutes, and democratize mobility access to wider populations. But delegation of control to automation is not without issues. One of the foreseen drawbacks is that users might experience negative emotional reactions to unanticipated or unexplainable automated maneuvers. In this paper we present a novel method to induce targeted emotional reactions, frustration and startle, in simulated automated driving environments. We describe the data collection process for 17 driver - passenger dyads and discuss the data labelling method for generating reliable novel emotion datasets. This contribution is a foundational methodology towards expanding emotional understanding in automated vehicles, a critical skill for building long-term trusted experiences.

Key Contributions

  • Presents method to induce driver emotions
  • Studies emotional reactions of driver-passenger dyads
  • Develops a reliable emotion labeling process
  • Achieves expert consensus on emotion labels
  • Provides methodology for emotional understanding

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Citation

@INPROCEEDINGS{8373886, author={Alyuz, Nese and Aslan, Sinem and Healey, Jennifer and Alvarez, Ignacio J. and Esme, Asli Arslan}, booktitle={2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)}, title={Towards Understanding Emotional Reactions of Driver-Passenger Dyads in Automated Driving}, year={2018}, volume={}, number={}, pages={585-592}, keywords={Labeling;Vehicles;Data collection;Cameras;Automation;Roads;affective computing;automated driving;drive simulation;labeling;inter-rater agreement}, doi={10.1109/FG.2018.00093} }
Alvarez, I. (2018). . 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).