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A Study on the Derivation of Risk Factors in Railway Site for the Improvement of Artificial Intelligence(AI)-Railway Safety System

AI기반 철도안전시스템 개선을 위한 철도현장 위험요소 도출에 관한 연구

  • Hoon Jung (Powermecca Co., Ltd.) ;
  • Sanghoon Lee (Dept. of Business Administration Hannam University) ;
  • Jangwook Kim (Korail Research Institute, Korea Railroad Corporation) ;
  • Sooyoung Kwon (Dept. of Digital Convergence Headquarters, Korea Railroad Corporation)
  • 정훈 (파워메카(주)) ;
  • 이상훈 (한남대학교 경영학과) ;
  • 김장욱 (한국철도공사 철도연구원) ;
  • 권수영 (한국철도공사 디지털융합본부)
  • Received : 2024.10.07
  • Accepted : 2024.10.16
  • Published : 2024.10.31

Abstract

The purpose of this study was to assess the problems of workers at railroad construction sites and suggest ways to ensure worker safety through the analysis of accidents and worker problems at these sites. First, the important worker safety factors in railway construction accidents were categorized into four types through focus group interviews (FGIs). Second, the factors that had the greatest impact on the problems related to railway sites and workers were identified by conducting surveys and interviews. The problems relating to each factor and ways to ensure safety at the railway sites were identified. Thus, it is believed that this study can provide important evidence for securing the safety of railroad workers and establishing an artificial intelligence (AI)-based railway safety system in the future.

본 연구는 철도종사자에 대한 철도사고 분석을 통해 철도현장 종사자의 문제점을 도출하고 작업자 안전성 확보방안을 제언하고자 한다. 첫째, 철도종사자들의 의견수렴을 거치는 FGI(Focus Group Interviews)를 통해 철도사고에서 중요한 작업자 안전성의 요인을 크게 4가지로 유형화한다. 철도현장 및 철도종사자 문제점과 관련이 깊은 안전설비, 위험차단, 작업시간 및 협의, 안전교육 등 4개 요인을 중심으로 20개 세부요인을 도출한다. 둘째, 철도현장의 종사자들을 방문하여 설문 조사와 인터뷰를 실시하였고, 이를 통해 철도현장 및 철도종사자 문제점과 관련한 요인 중 어떤 요인이 가장 큰 영향을 미치고, 어떤 요인이 영향을 미치지 않는지 규명한다. 결과적으로 철도종사자들이 생각하는 철도현장에서의 요인별 문제점과 안전성 확보방안을 도출한다. 따라서 본 연구는 향후 철도현장 작업자의 안전성 확보 및 인공지능 기반 철도안전시스템 구축을 위한 중요한 근거 자료로 활용될 수 있을 것으로 기대한다.

Keywords

Acknowledgement

본 연구는 국토교통부/국토교통과학기술진흥원의 R&D과제(사업명 : 철도 종사자의 인적오류 분석·평가·예방 기술개발) 지원으로 수행되었습니다.(과제번호 RS-2023-00239464).

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