• Title/Summary/Keyword: TCS 교통량/VDS 속도

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Analysis of Highway Traffic Indices Using Internet Search Data (검색 트래픽 정보를 활용한 고속도로 교통지표 분석 연구)

  • Ryu, Ingon;Lee, Jaeyoung;Park, Gyeong Chul;Choi, Keechoo;Hwang, Jun-Mun
    • Journal of Korean Society of Transportation
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    • v.33 no.1
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    • pp.14-28
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    • 2015
  • Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

A Study of Data Preprocessing Algorithm Using TCS/HI-PASS Data (TCS/HI-PASS 데이터를 이용한 전처리 알고리즘 구현에 관한 연구)

  • Jeong, Hyeon-Seok;Oh, Sang-Seok;Min, Sung-Gi
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.11a
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    • pp.1005-1008
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    • 2011
  • 본 논문에서는 교통 이력자료의 시공간 데이터를 활용하여 교통 분석 및 예측에 필요한 신뢰성 높은 데이터를 제공하기 위한 TCS/HI-PASS 전처리 알고리즘을 제안한다. 시공간 데이터의 전처리 알고리즘은 각종 교통정보에 이용되고 있으며, 그 중 대표적으로 활용되고 있는 것이 차량 검지기(VDS)를 통해 수집된 교통량, 속도, 점유율 정보이다. 이러한 정보에 가공처리 알고리즘을 적용하여 공간평균속도 기반의 통행시간을 산정하고 있으며, 고속도로 통행료 수납시스템(TCS)으로 부터는 출발영업소와 도착영업소의 진 출입시간을 기반으로 평균통행시간을 산정하고 있다. 본 연구에서는 차량 검지기(VDS) 데이터와 기존 TCS 데이터의 전처리 알고리즘을 분석하여 TCS와 HI-PASS 데이터 기반의 개선된 전처리 알고리즘을 설계, 구현하였다.