• 제목/요약/키워드: Highway-rail grade crossings

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건널목 개량제도에 관한 고찰 (The Study on Highway-Rail Grade Crossings Improvement System in Korea)

  • 이순철;방연근
    • 한국철도학회논문집
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    • 제8권4호
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    • pp.385-390
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    • 2005
  • In Korea, about 60 percent of railroad accidents are associated with highway-rail grade crossings numbering 1,657 nationwide, which the railroad system operates. To reduce the number of accidents, the authority formulated methods to improve or eliminate grade crossings. However, the improvement programs have made progress in slow time due to the institute inertia and the lack of funds from the municipal government, which shares the cost of improvement of grade crossings. Thus, this study analyses the institute system of the grade crossings, proposes modifications, and suggests financing methods to improve the grade crossings and to lower the number of accidents. Presently, the grade crossings safety perspective is directed towards road conditions and so a new perspective, which includes safety from the train perspective and to finance in review of railway system and to allocate the cost between the central government and the municipal governments. is discussed.

철도건널목의 사고예측모형 개발에 관한 연구 (Development and Application of Accident Prediction Model for Railroad At-Grade Crossings)

  • 조성훈;서선덕
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2001년도 추계학술대회 논문집
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    • pp.429-434
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    • 2001
  • Rail crossings pose special safety concerns for modern railroad operation with faster trains. More than ninety percent of train operation-related accidents occurs on at-grade crossings. Surest countermeasure for this safety hazard is to eliminate at-grade crossings by constructing over/under pass or by closing them. These eliminations usually require substantial amount of investment and/or heavy public protest from those affected by them. Thorough and objective analysis are usually required, and valid accident prediction models are essential to the process. This paper developed an accident prediction model for Korean at-grade crossings. The model utilized many important factors such as guide personnel, highway traffic, train frequency, train sight distance, and number of tracks. Developed model was validated with actual accident data.

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