Review of the impact of driving emotions on traffic safety:strategies for recognition and regulation
Negative emotions can result in driver distraction,delayed responses,and decision-making errors,thereby increasing the risk of traffic accidents.Investigating the effects of emotions on driving behavior and understanding the mechanisms that trigger these emotional responses is a critical focus in multidisciplinary research.This paper reviews and summarizes the theoretical foundations and research advancements concerning driving emotions by examining their impact on driving behavior,the mechanisms that trigger these emotions,and technologies for emotion recognition and regulation.It explores the mechanisms behind driving emotions and their correlation with driving behavior,emphasizing the specificity of emotional triggers among drivers and underscoring the importance of studying them.The paper summarizes the characteristics of driver emotion recognition and regulation strategies,highlighting both their applicability and limitations.Furthermore,it discusses emerging research trends to offer insights for the design and development of advanced driver assistance systems.Existing studies primarily focus on the impact of specific discrete emotions on driving behavior,with fewer investigations into the combined effects of multiple emotions.Moreover,the mechanisms by which personality traits,weather conditions,and various other factors influence driving emotions remain insufficiently understood.Emotion recognition in driving primarily relies on facial expressions,vocal tone,driving behavior,and physiological signals.However,the low robustness and accuracy of emotion recognition based on single features have led current research trends to shift towards multimodal feature fusion recognition.Among these approaches,the feature layer fusion strategy is most commonly employed,as it efficiently processes heterogeneous signals from multiple sources.Drivers can regulate their emotional states through visual,auditory,tactile,and olfactory stimulation.Notably,tactile and olfactory regulation methods have been shown to effectively reduce mental distractions for drivers,demonstrating significant benefits.These approaches can be incorporated into the driving assistance systems of intelligent cockpits.Research trends indicate that future studies should explore the mechanisms by which compound emotions affect driving behavior.Additionally,there should be a focus on how driving style and other factors synergistically trigger driving emotions,as well as an emphasis on the influence of personality traits and intelligent in-vehicle devices.It is essential to develop accurate driving risk prediction models based on driver behavior data,traffic conditions,and road information.By integrating multisource data for co-driving emotion recognition,real-time monitoring can be achieved.Moreover,developing intelligent automotive cockpits that engage emotionally and adjust driving experiences according to individual drivers'preferences,habits,and behavioral patterns is crucial.
safety livelihood sciencetraffic safetyemotionsdriving behaviorsafe driver assistance systems
万方数据
维普
