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http://dx.doi.org/10.22645/udi.2018.7.1.045

Forecasting of Motorway Traffic Flow based on Time Series Analysis  

Yoon, Byoung-Jo (인천대학교 도시과학대학 도시공학과)
Publication Information
Journal of Urban Science / v.7, no.1, 2018 , pp. 45-54 More about this Journal
Abstract
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.
Keywords
Motorway; Forecasting of Traffic Flow; Time Series Analysis;
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