The Induction and Detection Method of Angry Driving: Evidences from EEG and Physiological Signals

Abstract

Introduction. Angry driving has been a significant road safety issue worldwide. This study focuses on the problem of inducing and detecting driving anger based on the simulation and on-road experiments. Methods. First, three typical scenarios (including waiting for the red light frequently, traffic congestion, and the surrounding vehicle interference) which could cause driving anger were developed and applied in a driving simulator experimental study. The self-reported, biosignals, and brain signals of driving anger data were collected from the driving anger induction experiment. Second, in order to examine the difference of driving anger between simulation driving and real-life driving, 22 groups of on-road experiments were conducted. The typical scenes and self-reported data were recorded to distinguish normal driving from angry driving. Finally, a Hidden Naïve Bayes classifier was employed to detect angry driving during the on-road driving according to the four features (namely, BVP, SC, %, and %) from driver's biosignals and brain signals. Results. The evaluation of emotional differentiation degrees and emotional intensity indicates that the developed scenarios based on virtual reality were useful and effective in inducing driving anger. Meanwhile, the proposed angry driving detection approach achieves an accuracy of 85.0%. Conclusions and Applications. Due to possible crash and injury from the on-road experiments, the proposed approach of driving anger induction using a driving simulator is effective in exploring the causal relationship between angry driving, unsafe driving behavior, and traffic accident. In addition, angry driving detection approach can provide theoretical foundation for the development of driving anger warning products.

The role of anger rumination as a mediator in the relationship between driver moral disengagement and driving angry

“…Drivers tend to employ moral disengagement to rationalize their behavior, expressing driving anger through anger rumination. Consequently, the rates of anger induction and average anger levels are relatively high in such scenarios [ 38 , 43 ]. In contrast to the above two scenarios, sudden braking by preceding vehicles and pedestrians crossing the road incidents are mostly random events with relatively low potential threats.…”

“…Assessing whether anger rumination and moral justifications reliably predict driving anger in real-world driving situations poses a challenge, primarily because investigations into anger rumination and driving anger, as well as studies on moral justifications linked to aggressive driving, have predominantly relied on questionnaire-based methodologies. As this limitation and the effectiveness of driving simulators in eliciting anger [ 11 , 38 ], the present study adopted five traffic scenarios simulated by driving simulators—a traffic jam, pedestrian crossing, sudden halt by the vehicle in front, opposing vehicle reversing direction, and another vehicle abruptly entering the road—as means to provoke driving anger. The study's objective was to ascertain whether moral disengagement and anger rumination serve as principal psychological triggers for driving anger, and hypothesized that there are differences in the psychological triggers that play a major role in driving anger in different road situations (Hypothesis 1).…”

Analyzing the impact of Driving tasks when detecting emotions through brain–computer interfaces

“…In addition, it was concluded that music has a great power to influence human emotions, making them a great mechanism to control them. On the other hand, Yan et al [23] sought to detect a negative or angry emotional state in drivers when confronted with driving situations that usually elicited these modes, for example, a red traffic light. For this purpose, they used Hidden Naı ¨ve Bayes (BVP), obtaining 85% accuracy.…”

Regulating road rage

“…Research from both on‐road and simulated driving experiments has demonstrated that road rage is associated with increased heart rate, skin conductance, and respiration rate, as well as altered beta‐waves and delta‐waves (Galovski, Blanchard, Malta, & Freidenberg, 2003; Herrero‐Fernández, 2016; Wan, Wu, Lin, & Ma, 2017; Yan, Wan, Qin, & Zhu, 2018). Behaviorally, Deffenbacher, Lynch, Oetting, and Swaim (2002) have identified three ways people express road rage (which are associated with road rage appraisals): verbal behavior (e.g., cursing); physical expression using one's body (e.g., stepping outside the car to engage in a physical fight); and physical expression using one's own car (e.g., honking).…”