Trait Anger Cause Risky Driving Behavior by Influencing Executive Function and Hazard Cognition

Road rage is a serious phenomenon around the world in the driving context and may contribute to risky driving behavior, further increasing the probability of collisions. Among several factors, trait anger is the most relevant variable towards road rage. This research aims to interpret how trait anger influences risky driving behavior in detail. We used an online questionnaire, which contains trait anger scale (TAS), executive function index (EFI), hazard cognition scale (HCS; represents attitudes towards risky driving behavior), driver behavior questionnaire (DBQ), and self-reported traffic violations (e.g., accidents, penalty points, fines). The linear regression model showed that trait anger is a medium but statistically significant predictor of risky driving behavior and drivers’ attitude towards risky situations can significantly predict risky driving behavior in statistics up to medium effect. But risky driving behavior cannot be predicted by executive function. Interestingly, for the objective indicators, the zero-inflated Poisson regression or negative binomial regression results suggested that age is a small protective factor towards accidents/penalty points/fines, and trait anger also is a small protective factor in accidents/fines. While executive function alleviates penalty points and fines, whereas hazard cognition alleviates penalty points only. They all represented a small effect on risky driving behavior. Path analysis suggested that trait anger influences risky driving behavior through executive function and hazard cognition. This study provides a theoretical framework for further research about road rage and offers some possible intervene towards road rage.

Hand-ling ‘road rage’

Although mobility and movement has recently gained importance within interactionist studies of social action, not much is known about the consequentiality of being on the move for the particular unfolding of interactional episodes. Utilising two publicly accessible video clips of ‘road rage’ situations, we describe and analyse the centrality of hand-work in the escalation and decline of an emotionally charged interaction between members of traffic. Avoiding an a priori cognitivist stance, we show in detail how the work of hands can be constitutive of anger itself, and that it can lead to open conflict on the boundary of physical violence.

Vision-Based Road Rage Detection Framework in Automotive Safety Applications

Drivers’ road rage is among the main causes of road accidents. Each year, it contributes to more deaths and injuries globally. In this context, it is important to implement systems that can supervise drivers by monitoring their level of concentration during the entire driving process. In this paper, a module for Advanced Driver Assistance System is used to minimise the accidents caused by road rage, alerting the driver when a predetermined level of rage is reached, thus increasing the transportation safety. To create a system that is independent of both the orientation of the driver’s face and the lighting conditions of the cabin, the proposed algorithmic pipeline integrates face detection and facial expression classification algorithms capable of handling such non-ideal situations. Moreover, road rage of the driver is estimated through a decision-making strategy based on the temporal consistency of facial expressions classified as “anger” and “disgust”. Several experiments were executed to assess the performance on both a real context and three standard benchmark datasets, two of which containing non-frontal-view facial expression and one which includes facial expression recorded from participants during driving. Results obtained show that the proposed module is competent for road rage estimation through facial expression recognition on the condition of multi-pose and changing in lighting conditions, with the recognition rates that achieve state-of-art results on the selected datasets.

An Evolutionary Science Perspective on Intuition, Rationality, Conflict, and Moral Judgments

Moral judgments can be the result of cognitive deliberations, which develop with age and socialization. Rationality began in humans with the development of the cerebral cortex. Alternatively, they can be the based-on survival mechanisms emanating in the sympathetic nervous based on innate, survival mechanisms (fight, flight, freeze) and the amygdala. Common examples are road rage (e.g., I was right while the other driver was wrong, cut me off, and could have killed me) and hold-your-ground state laws for self-defense (the victim was justified in killing the intruder, even though the intruder had no weapon when reaching into their coat pocket). Moral decision making can be based on an innate survival mechanism. Those who did this did not survive and were not our ancestors. This chapter reviews the research on signal detection theory, how aggression is favored over conciliation, as cognitive reasoning breaks down. Physiological studies involving the sympathetic and parasympathetic nervous system are reviewed in terms of the amygdala and emotional intelligence.

Reduce the occurrence of “road rage” and ensure the safety of self-driving travel passengers

With the rapid growth of car ownership today, choosing self-driving travel has become the first choice for many people. At the same time, we should pay attention to the safety issues in the process of self-driving travel. The “road rage” emotions of self-driving drivers during the driving process pose a threat to the safety of the individual driver and the passengers in the car. Based on the traffic-oriented intelligent terminal and system platform, this article explores ways to reduce the emotion of “road rage” from the perspective of management and control. The methods discussed in this article can also help reduce environmental pollution and ensure travel safety.