This study begins with the recognition that, despite the continued decline in overall traffic accidents, public perceptions of safety remain low due to the rising number of accidents involving elderly individuals and nighttime pedestrians, the lack of...
This study begins with the recognition that, despite the continued decline in overall traffic accidents, public perceptions of safety remain low due to the rising number of accidents involving elderly individuals and nighttime pedestrians, the lack of expertise in accident investigations, and the complexity and inefficiency of current handling procedures. In response, the study analyzes traffic accident handling procedures and the application of artificial intelligence (AI) technologies in the United States and Europe to explore advanced traffic accident response systems that can be applied in the Korean context. The findings indicate that AI-based traffic accident investigation support systems play a crucial role in enhancing the speed and accuracy of the entire response process—from incident detection and cause analysis to accident simulation and legal liability assessment. Furthermore, the study shows that these systems can significantly contribute to predicting high-risk accident zones and establishing tailored safety policies. However, since the study is primarily theoretical and based on foreign case studies, empirical validation and in-depth analysis of technical and institutional constraints in the Korean setting are necessary. Future research should address the field applicability, legal reliability, data protection concerns, and response strategies for vulnerable populations in greater detail. This study serves as a foundational reference for the digital transformation of traffic accident response systems and the development of traffic safety policies that align with public expectations.