Information Modeling of Railway Track using Information Iinkage of Railway Alignment and Alignment-based Objects

철도 선형중심의 객체 정보연계를 통한 철도 궤도부 정보모델 생성 방안

  • Kwon, Tae Ho (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Park, Sang I. (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Shin, Min Ho (Advanced Infrastructure Research Team, Korea Railroad Research Institute) ;
  • Lee, Sang-Ho (School of Civil and Environmental Engineering, Yonsei Univ.)
  • 권태호 (연세대학교 토목환경공학과) ;
  • 박상일 (연세대학교 토목환경공학과) ;
  • 신민호 (한국철도기술연구원 첨단인프라연구팀) ;
  • 이상호 (연세대학교 토목환경공학과)
  • Received : 2017.10.30
  • Accepted : 2017.11.13
  • Published : 2017.12.29


As BIM has been widely used in the field of architecture, efforts to apply BIM to civil engineering structures are increasing rapidly. Since commercial BIM softwares are focused on building structure, it is difficult to apply to alignment-based civil infrastructures. In this study, we proposed a method to generate an information model that reflects cant by sharing information between alignment-centered modeling tools and BIM authoring tools to manage information of railway track. The railway track modeling process consists of classifying structures into continuous and non-continuous structures, creating continuous structures by alignment-centered modeling tools, and using the shared alignment information to generate information model of the non-continuous structures. Non-continuous structures were generated by an algorithm that calculates the position and rotation information of each structure based on discretized railway alignment and cant information transmitted to the BIM authoring tools. The availabilities of proposed method were studied by applying to the osong test-line. Using the test model, it was shown that the objects were identified, the properties were extracted, and the quantities of each structure were calculated.


Supported by : 국토교통부


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  1. The Information Modeling Method based on Extended IFC for Alignment-based Objects of Railway Track vol.31, pp.6, 2018,