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http://dx.doi.org/10.15683/kosdi.2018.06.30.230

A Study on the Prediction of Traffic Volume on Highway by the Reference Day of Archived Data  

Lee, So-Yeon (Dept. of Urban Eng., Incheon National Univ)
Jung, So-Yeon (Dept. of Urban Eng., Incheon National Univ)
Publication Information
Journal of the Society of Disaster Information / v.14, no.2, 2018 , pp. 230-237 More about this Journal
Abstract
Purpose: In Korea, traffic information is collected in real time as part of Intelligent Transportation System to enhance efficiency of road operation. However, traffic information based on real-time data is different from the traffic situation the driver will experience. Method: In this study, forecasts were made for future highway traffic by day and time period by adjusting the Archived data reference days to 3, 5 and 10 days based on existing traffic Archived data. Results: Fewer days of reference in the past showed smaller errors. The prediction of Monday based on five past histories showed greater errors than the 10 past histories, as the traffic flow on the sixth Monday of 2016 was somewhat different from the usual holiday. Conclution: This study shows that less of the reference days of the past history when estimating traffic volume, the more accurate the data of the traffic history of the event can be used on special days.
Keywords
ARIMA Models; Freeway; Traffic volume prediction; Short-term prediction; MAPE;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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