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http://dx.doi.org/10.7470/jkst.2015.33.3.256

Development of a Mid-/Long-term Prediction Algorithm for Traffic Speed Under Foggy Weather Conditions  

JEONG, Eunbi (Department of Transportation and Logistics Engineering, Hanyang University at Ansan)
OH, Cheol (Department of Transportation and Logistics Engineering, Hanyang University at Ansan)
KIM, Youngho (Department of Transportation Safety and Highway Research, The Korea Transport Institute)
Publication Information
Journal of Korean Society of Transportation / v.33, no.3, 2015 , pp. 256-267 More about this Journal
Abstract
The intelligent transportation systems allow us to have valuable opportunities for collecting wide-area coverage traffic data. The significant efforts have been made in many countries to provide the reliable traffic conditions information such as travel time. This study analyzes the impacts of the fog weather conditions on the traffic stream. Also, a strategy for predicting the long-term traffic speeds is developed under foggy weather conditions. The results show that the average of speed reductions are 2.92kph and 5.36kph under the slight and heavy fog respectively. The best prediction performance is achieved when the previous 45 pattern cases data is used, and the 14.11% of mean absolute percentage error(MAPE) is obtained. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.
Keywords
fog; fog intensity; linear regression; long-term prediction; travel speed prediction;
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Times Cited By KSCI : 2  (Citation Analysis)
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