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

• Published in: International journal of human-computer studies Vol. 69; no. 9; pp. 571 - 586
• Main Authors: Cai, Hua, Lin, Yingzi
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-08-2011; Elsevier
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Driving simulation; Emotion assessment; Emotion elicitation; Emotion model; Emotion–performance relation; Exact sciences and technology; Human performance modeling; Simulation; Software; Emotion–performance relation; Emotion model; Emotion assessment; Driving simulation; Emotion elicitation; Human performance modeling; Performance evaluation; Computer simulation; Man machine system; Vehicle driving; Psychology; Emotion emotionality; Modeling; Emotion elicitation: Emotion assessment; Multiagent system; Emotion-performance relation; User interface; Arousal; Virtual reality; Elicitation; Artificial intelligence; Intelligent system
• ISSN: 1071-5819; 1095-9300
• DOI: 10.1016/j.ijhcs.2011.05.003

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.
► Operators' task performance depends on emotion's 2-dimensional components. Inverted U-shaped relationship between task performance and emotional arousal. ► Inverted U-shaped relationship between task performance and emotional valence. ► Arousal and valence are not perfectly independent in the entire 2-D emotion plane. ► Psychological “sweet spot” depends on appropriate emotional arousal and valence.