"基于多模态融合的驾驶人愤怒情绪识别方法研究"

The research on driver anger emotion recognition method based on multimodal fusion addresses the importance of identifying and understanding the emotional state of drivers in order to enhance traffic safety. When a driver is experiencing anger, their cognitive abilities and driving performance are adversely affected, increasing the risk of accidents and injuries. This study aims to develop a comprehensive method for detecting driver anger by integrating various modalities such as facial expressions, voice tone, and driving behavior. By analyzing these different signals, researchers can accurately assess the emotional state of a driver and implement timely interventions to prevent potential risks on the road. The findings of this research contribute to the advancement of driver assistance systems and the promotion of safer driving practices.