• Title/Summary/Keyword: 톨게이트 유출입교통량

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Construction of vehicle classification estimation model from the TCS data by using bootstrap Algorithm (붓스트랩 기법을 이용한 TCS 데이터로부터 차종별 교통량 추정모형 구축)

  • 노정현;김태균;차경준;박영선;남궁성;황부연
    • Journal of Korean Society of Transportation
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    • v.20 no.1
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    • pp.39-52
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    • 2002
  • Traffic data by vehicle classification is difficult for mutual exchange of data due to the different vehicle classification from each other by the data sources; as a result, application of the data is very limited. In Particular. in case of TCS vehicle classification in national highways, passenger car, van and truck are mixed in one category and the practical usage is very low. The research standardize the vehicle classification to convert other data and develop the model which can estimate national highway traffic data by the standardized vehicle classification from the raw traffic data obtained at the highway tollgates. The tollgates are categorized into several groups by their features and the model estimates traffic data by the standardized vehicle classification by using the point estimation and bootstrap algorithm. The result indicates that both of the two methods above have the significant level. When considering the bias of the extreme value by the sample size, the bootstrap algorithm is more sophisticated. Using result of this study, we is expect the usage improvement of TCS data and more specific comparison between the freeway traffic investigation and link volume on freeway using the TCS data.