Modeling of operators' emotion and task performance in a virtual driving environment

  • Authors:

  • Hua Cai;Yingzi Lin

  • Affiliations:

  • Mechanical and Industrial Engineering Department, Northeastern University, Boston, MA 02115, USA;Mechanical and Industrial Engineering Department, Northeastern University, Boston, MA 02115, USA

  • Venue:
  • International Journal of Human-Computer Studies
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Emotional human-computer interactions are attracting increasing interest with the improvement in the available technology. Through presenting affective stimuli and empathic communication, computer agents are able to adjust to users' emotional states. As a result, users may produce better task performance. Existing studies have mainly focused on the effect of only a few basic emotions, such as happiness and frustration, on human performance. Furthermore, most research explored this issue from the psychological perspective. This paper presents an emotion and performance relation model in the context of vehicle driving. This general emotion-performance model is constructed on an arousal-valence plane and is not limited to basic emotions. Fifteen paid participants took part in two driving simulation experiments that induced 115 pairs of emotion-performance sample. These samples revealed the following: (1) driving performance has a downward U-shaped relationship with both intensities of arousal and valence. It deteriorates at extreme arousal and valence. (2) Optimal driving performance, corresponding to the appropriate emotional state, matches the ''sweet spot'' phenomenon of the engagement psychology. (3) Arousal and valence are not perfectly independent across the entire 2-D emotion plane. Extreme valence is likely to stimulate a high level of arousal, which, in turn, deteriorates task performance. The emotion-performance relation model proposed in the paper is useful in designing emotion-aware intelligent systems to predict and prevent task performance degradation at an early stage and throughout the human-computer interactions.