차량돌진의 위험성과 물리적 보안 장치의 발전 방향 분석

Abstract

With the advancement of science and technology, the risk of vehicle ramming incidents is increasing, primarily due to technical defects in autonomous vehicles and the threat of unauthorized remote control. Vehicle ramming has emerged as a criminal tool, giving rise to a new form of terrorism known as vehicle ramming terrorism. This study aims to analyze the risks associated with vehicle ramming and to propose effective mitigation strategies. Characterized as a low-tech form of crime, vehicle ramming entails indiscriminate attacks on crowds or specific targets, and its frequency has risen globally in recent years. The advancement of autonomous driving technology further exacerbates these risks, underscoring the necessity for effective physical security measures. This study defines vehicle ramming risk as ‘the potential for physical collisions involving vehicles, whether intentional or accidental, that can lead to loss of life and property damage.’Based on this definition, the study categorizes physical security devices into passive and active types. The research emphasizes the importance of conducting environment-specific vulnerability assessments and developing appropriate designs for structural physical security devices, advocating for creating an efficient integrated physical security system. It explores the potential of leveraging AI technology to establish preliminary environmental assessment tools at the private sector level and develop national-level physical security systems and innovative security solutions. Current literature frequently omits intentionality analysis and focuses mainly on particular case studies, resulting in partial risk assessments. Future research should focus on developing a framework that integrates the analysis of both intentional and unintentional vehicular incidents. Additionally, there is a need for a comprehensive risk assessment model that considers various environmental factors, enabling the provision of customized physical security solutions tailored to specific regions and situations. Furthermore, advancing towards developing a real-time risk analysis and prediction system, leveraging AI and cutting-edge technologies, will be a vital direction for future research.