The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Estimation of Expressway O/D Matrices from TCS data by Using Video Survey Data for Vehicle Classification: Focused on Truck

차종구분 영상조사 자료를 활용한 TCS기반 고속도로 O/D 구축: 화물자동차 중심으로

  • 신승진 (서울시립대학교 교통공학과) ;
  • 박동주 (서울시립대학교 교통공학과) ;
  • 최윤혁 (한국도로공사 도로교통연구원) ;
  • 정소영 (한국도로공사 도로교통연구원) ;
  • 허은진 (한국도로공사 도로교통연구원) ;
  • 하동익 (서울대학교 건설환경종합연구소)
  • Received : 2012.07.19
  • Accepted : 2013.02.13
  • Published : 2013.02.28
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Abstract

Truck demand analysis based on TCS data has limitation in that TCS data can not provide truck O/D data for each type of truck vehicle. This study conducted video survey for classifying truck vehicle types. By using TCS data and vehicle ratio by region/cities type, truck O/D data on expressway were estimated. It was found that average travel distances of small truck, medium truck and large truck were 52km/veh, 56km/veh and 97km/veh, respectively by analysing truck O/D data estimated in this study. The reliability analysis showed that check points where error rate is lower than 30% comprise of 87.3%. It is considered that estimated O/D data by truck vehicle types would be useful for the analysis of truck demand of expressway.

TCS자료를 통한 고속도로 화물자동차 수요추정은 많은 한계가 있다. 본 연구는 TCS자료의 차종을 재분류하기 위한 영상조사를 수행하여 고속도로 도시유형별/권역별 차종비율을 분석하였다. 또한, 도시유형별/권역별 차종비율과 TCS자료를 활용하여 2011년 기준 TCS기반 고속도로 화물자동차 O/D를 구축하였다. 본 연구에서 구축한 고속도로 화물자동차 O/D분석결과, 화물자동차 톤급별 평균통행거리는 소형화물차 52km/대, 중형화물차 56km/대, 대형화물차 97km/대로 나타났다. 또한 전국 고속도로를 대상으로 관측교통량과 배정교통량의 오차율이 30% 이하인 관측지점은 전체 관측지점의 87.3%로 나타났다. 본 연구는 고속도로 화물자동차 수요추정을 위한 차종별 고속도로 O/D 구축이라는 점에서 의미가 있으며, 고속도로 장래화물수요예측에 크게 기여할 것으로 판단된다.

Keywords

References

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