• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2022, Vol. 58 ›› Issue (22): 379-394.doi: 10.3901/JME.2022.22.379

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Analysis of the Influence Mechanism of Driver’s Emotion on Driving Risk

LI Wen-bo1,2, LIU Yu-jing1, ZHANG Jun-cheng1, XIAO Hua-fei1, GUO Gang1, CAO Dong-pu2   

  1. 1. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044;
    2. School of Vehicle and Mobility, Tsinghua University, Beijing 100084
  • Received:2022-01-20 Revised:2022-08-03 Online:2022-11-20 Published:2023-02-07

Abstract: Reducing the emotion-caused accidents risk by studying driver's emotion has been an emergency topic in multidisciplinary research. By qualitatively analyzing the relationship between driver emotion, driving behavior and driving risk, the mechanism of how emotion affects driving risk is expounded, and the driving risk calculation model is built. To quantitatively analyze the relationship between driver emotion, driving behavior and driving risk, this study collects a library of driver emotion induction materials, and conducts driving data collection experiments under various driver's emotions. Then, the impact of driver's different emotions on driving behavior is analyzed. Finally, by mapping the relationship between driving behavior and driving risk, the influence mechanism of driver emotion on driving risk is analyzed. The results show that for discrete emotions, anger, fear, sadness, surprise,and disgust have a higher high-risk ratio; while neutral and happy have a lower high-risk ratio. For dimensional emotions, on the three dimensions of valence, arousal and dominance, low valence and high valence, low arousal and high arousal, low dominance and high dominance have a higher high-risk ratio. The results of the mechanism of driver's emotion-driving risk will provide an important basis for designing recognition schemes and regulation strategies for different driver's emotions, which is significant to decision-making and planning of intelligent connected vehicles.

Key words: driver emotion, driving behavior, driving risk, intelligent cockpit, intelligent connected vehicles

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