도시과학 (Journal of Urban Science)

인천대학교 도시과학연구원 (Urban Science Institute)
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시계열 분석을 활용한 고속도로 교통류 예측

Forecasting of Motorway Traffic Flow based on Time Series Analysis

  • 윤병조 (인천대학교 도시과학대학 도시공학과)
  • 투고 : 2018.06.19
  • 심사 : 2018.06.30
  • 발행 : 2018.06.30
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초록

The purpose of this study is to find the factors that reduce prediction error in traffic volume using highway traffic volume data. The ARIMA model was used to predict the day, and it was confirmed that weekday and weekly characteristics were distinguished by prediction error. The forecasting results showed that weekday characteristics were prominent on Tuesdays, Wednesdays, and Thursdays, and forecast errors including MAPE and MAE on Sunday were about 15% points and about 10 points higher than weekday characteristics. Also, on Friday, the forecast error was high on weekdays, similar to Sunday's forecast error, unlike Tuesday, Wednesday, and Thursday, which had weekday characteristics. Therefore, when forecasting the time series belonging to Friday, it should be regarded as a weekly characteristic having characteristics similar to weekend rather than considering as weekday.

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참고문헌

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