The increasing incidence of traffic accidents triggered by "road rage" poses a significant threat to public safety. Therefore, an in-depth analysis of its mechanisms and influencing factors is imperative. Previous research indicates that factors inducing driving anger include personal characteristics (such as age, gender, and temperament) and situational stimuli (such as traffic lights, hostile behaviors from surrounding vehicles, and overall traffic conditions). Building on this, the current study utilized naturalistic driving experiments with taxi drivers as subjects and employed a structural equation model to quantitatively analyze the interrelationships among these factors and to calculate the impact weights of personal characteristics and situational stimuli on driving anger. The results indicate that temperament, traffic flow conditions, behaviors of other traffic participants, and traffic signals are positively correlated with driving anger, whereas gender shows a negative correlation. Age, while not significantly correlated with anger, is negatively associated with temperament. Additionally, traffic conditions, traffic signals, and participant behaviors exhibit significant negative correlations with anger. These findings provide theoretical support for traffic management authorities in addressing road rage.
Path analysis of the factors influencing driving anger among taxi drivers based on naturalistic driving data
Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024) ; 2024 ; Guangzhou, China
Proc. SPIE ; 13286
2024-09-30
Conference paper
Electronic Resource
English
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