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K-factor Prediction in Import and Export Cargo Trucks-Concentrated Expressways by Short-Term VDS Data

단기 VDS자료로 수출입화물트럭이 집중하는 고속도로의 K-factor 추정에 관한 연구

  • Kim, Tae-Gon (Civil Engineering, Korea Maritime and Ocean University) ;
  • Heo, In-Seok (Civil Engineering, Korea Maritime and Ocean University) ;
  • Jeon, Jae-Hyun (Civil Engineering, Korea Maritime and Ocean University)
  • 김태곤 (한국해양대학교 건설공학과) ;
  • 허인석 (한국해양대학교 토목환경공학과) ;
  • 전재현 (한국해양대학교 토목환경공학과)
  • Received : 2013.11.01
  • Accepted : 2014.02.11
  • Published : 2014.02.28

Abstract

Gyeongbu and Namhae expressways in the country, are the major arterial highways which are connected with the Busan port in the north-south and east-west directions, respectively, and required to study the traffic characteristics about the hourly volume factors(K-factor) by concentrated midium-size and large-size cargo trucks of 20% or higher in expressways. We therefore attempted to predict the K-factor in expressways through the correlation analysis between K-factor and K-factor estimates on the basis of the short-term VDS data collected at the basic segments of the above major expressways. As a result, power model appeared to be appropriate in predicting K-factor by the K-factor estimate based on VDS data for 7 days with a high explanatory power and validity.

국내 경부고속도로와 남해고속도로는 부산항을 각각 남북방향과 동서방향으로 연계하며 20%이상의 중대형화물트럭 혼재율과 특정시간대 통행량이 집중되는 핵심 간선도로로 시간교통량계수(K-factor)에 대해 연구의 필요성을 깨닫게 되었다. 그리하여 본 연구에서는 경부고속도로와 남해고속도로의 기본구간에서 단기간동안 수집된 차량검지시스템(vehicle detection system, VDS)자료를 이용하여 고속도로의 K-factor와 K-factor추정치(estimate)사이의 상관분석을 통해서 고속도로의 K-factor추정모형 구축을 목적으로 연구하였다. 결과적으로 7일 VDS자료의 K-factor추정치(estimate)와 함께 파워(POW)모형이 K-factor를 추정에 높은 설명력과 신뢰성이 있음을 확인할 수 있었다.

Keywords

References

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