How appraisals shape driver emotions: A study from discrete and dimensional emotion perspectives

• The goal relevance feature is the most significant predictor of valence.
• The arousal level of the provoked emotion is highest in other-blame situations.
• The arousal is higher when a driver is uncertain about the outcome than when he is certain.
• Fear is associated with outcome certainty while anxiety is associated with uncertainty.

This study aimed to investigate how the emotional responses of drivers, from both dimensional and discrete perspectives, may be predicted by using the appraisal components of goal relevance, blame party, and certainty. Traffic scenarios representing a combination of the three appraisal components were designed and presented to participants. The emotional responses to each scenario were measured on an Arousal–Valence emotional space and were assigned with discrete emotion labels by applying a cluster analysis. For the dimensional model, the results showed that valence was significantly associated with the blame party and the goal relevance components. The arousal was, as hypothesised, predicted by the blame party and the certainty components. For the discrete model, it was found that driving anger was most likely to be provoked when other drivers were responsible for the adverse driving outcome; driving fear was most commonly experienced in situations where driver safety was threatened by the driver himself/herself or by impersonal circumstance; and driving anxiety was an outcome of uncertain arrival-blocking events caused by driver himself/herself or impersonal circumstance. Findings from this study suggest the feasibility of predicting emotional dimensions on the basis of the appraisal process. Moreover, this study contributes to the research on driver emotion by demonstrating that the certainty feature of traffic events plays an important role in determining the emotional responses of drivers.