The slow and the furious: Anger, stress and risky passing in simulated traffic congestion

• Published in: Transportation research. Part F, Traffic psychology and behaviour Traffic psychology and behaviour, 2016-10, Vol.42, p.1-14
• Main Authors: Emo, Amanda K., Matthews, Gerald, Funke, Gregory J.
• Format: Article
• Language: English
• Subjects: Aggression; Aggressiveness; Anger; Computer simulation; Coping; Driver behavior; Driving conditions; Mathematical models; Moods; Multivariate analysis; Risk taking; State anger; Stress; Stresses; Traffic congestion; Traffic engineering; Traffic flow; Trait anger
• ISSN: 1369-8478; 1873-5517
• DOI: 10.1016/j.trf.2016.05.002

•Anger, aggression, coping and stress are overlapping sources of risk in driving.•A simulator study compared anger and other factors as predictors of risky passing.•Driving in slow traffic elicited both anger and stress.•Confrontive coping was a stronger predictor of risky passing than anger and stress.•Interventions should address habitual coping styles as well as mitigating anger. 112 college students participated in a study of simulated driving to investigate how trait driver aggression, state anger and coping predict risk-taking behaviors such as tailgating and frequency of passing. The simulation scenario, driving in slow traffic, elicited both anger and stress. However, consistent with the transactional model of driver stress, anger and distress were associated with different patterns of coping. Both anger and aggression were associated with dispositional confrontive coping. Drivers were afforded opportunities to pass other traffic, in risky circumstances. Dispositional coping factors, especially confrontive coping, predicted risk-taking behaviors, such as frequent passing and tailgating prior to the pass. However, trait aggression and anger did not predict risky behaviors. Confrontive drivers may have developed habitual behavioral styles that are expressed irrespective of current mood and coping strategy. The findings suggest that stress or anger management may be only a partial solution to dangerous driving in congested conditions. Further investigation of how drivers acquire confrontive behavioral styles is needed. The data also support multivariate approaches to selecting safe drivers in commercial and industrial contexts.