인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
In recent years, bicycle-related traffic collisions have occurred more frequently with the increasing use of bicycles, which highlights an urgent need for systematic monitoring and safety measures. In contrast to vehicle traffic monitoring systems, relatively little data has been collected on bicycle traffic. To that end, the application of intelligent closed-circuit television (CCTV) to support crash prevention and response has attracted attention as a topic of considerable interest. In this study, the suitability of intelligent CCTV locations for monitoring the risk of bicycles being involved in traffic collisions was evaluated in Gimhae, South Korea. The analysis incorporated 17 variables across six categories, including population, traffic volume and speed, land use, road structure and environment, bicycle infrastructure, and data on collisions. A negative binomial regression model was applied to predict the frequency of bicycle traffic collisions. A total of 79 high-risk grids were identified based on the analysis. These were primarily concentrated in central districts such as Hoehyeon- dong with additional areas in Jangyu-dong, which indicates a need for enhanced bicycle traffic monitoring. The results of a comparison with existing intelligent CCTV locations revealed that many of the identified high-risk areas are not covered sufficiently by the field of view of currently installed CCTV systems, which highlights some notable limitations of the existing monitoring system. This study provides a set of spatial adjustments to the placement of CCTV cameras to enhance real-time collision detection and response while contributing to the development of region-specific safety measures based on accumulating additional CCTV data.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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