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보행자-차량 충돌사고 특성분석 방법론 비교 연구

Comparison of Methodologies for Characterizing Pedestrian-Vehicle Collisions

  • 최새로나 (한양대학교 교통.물류공학과) ;
  • 정은비 (한양대학교 교통.물류공학과) ;
  • 오철 (한양대학교 교통.물류공학과)
  • Choi, Saerona (Department of Transportation and Logistics Engineering, Hanyang University) ;
  • Jeong, Eunbi (Department of Transportation and Logistics Engineering, Hanyang University) ;
  • Oh, Cheol (Department of Transportation and Logistics Engineering, Hanyang University)
  • 투고 : 2013.07.08
  • 심사 : 2013.11.28
  • 발행 : 2013.12.31

초록

최근 운전자의 보행자-차량 충돌사고 감소를 목적으로 한 다양한 연구가 수행되고 있으며, 본 연구에서는 보행자-차량 사고 발생 특성 및 심각도 영향요인 분석을 위하여 다양한 분석방법론을 활용한 보행자 교통사고 분석을 수행하였다. 통계모형과 휴리스틱모형 적용시 각 기법에 따른 결과를 도출함으로써 보행자 사고분석시 분석목적에 적합한 방법론을 제시하는 것을 목적으로 하였다. 이를 위하여 최근 3년간 발생한 경기도 교통사고자료(2008-2010년)를 활용하여 보행자 교통사고의 발생특성을 분석하였다. 또한, 통계모형인 이항 로지스틱 회귀분석, 순서형 프로빗 모형을 이용하여 보행자 교통사고 심각도 증가에 통계적으로 유의한 영향을 미치는 변수를 도출하였으며, 휴리스틱모형인 서포트 벡터 머신, 의사결정나무를 적용하여 교통사고 심각도 분류를 위한 모형을 개발하고 그 결과를 비교분석 하였다. 본 연구의 분석결과는 보행자 교통안전분석의 기초자료로 활용할 수 있으며 향후 국내 보행자-차량 충돌사고 분석시 유용하게 활용될 수 있을 것으로 기대된다.

The major purpose of this study is to evaluate methodologies to predict the injury severity of pedestrian-vehicle collisions. Methodologies to be evaluated and compared in this study include Binary Logistic Regression(BLR), Ordered Probit Model(OPM), Support Vector Machine(SVM) and Decision Tree(DT) method. Valuable insights into applying methodologies to analyze the characteristics of pedestrian injury severity are derived. For the purpose of identifying causal factors affecting the injury severity, statistical approaches such as BLR and OPM are recommended. On the other hand, to achieve better prediction performance, heuristic approaches such as SVM and DT are recommended. It is expected that the outcome of this study would be useful in developing various countermeasures for enhancing pedestrian safety.

키워드

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피인용 문헌

  1. 순서형 프로빗 모형을 이용한 버스 운송사업 유형 별 사고심각도 영향요인 분석 vol.36, pp.1, 2013, https://doi.org/10.7470/jkst.2018.36.1.013
  2. 철도 유형별 사고 심각도 영향 요인 분석 vol.21, pp.6, 2018, https://doi.org/10.7782/jksr.2018.21.6.604