TY  - JOUR
PY  - 2015//
TI  - Development of a mid-/long-term prediction algorithm for traffic speed under foggy weather conditions
JO  - Journal of Korean Society of Transportation
A1  - Jeong, Eunbi
A1  - Oh, Cheol
A1  - Kim, Youngho
SP  - 256
EP  - 267
VL  - 33
IS  - 3
N2  - 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 ; 안개; 안개정도; 선형회귀분석; 중장기 예측; 통행속도 예측<p />  <p>Language: ko</p>
LA  - ko
SN  - 1229-1366
UR  - http://dx.doi.org/10.7470/jkst.2015.33.3.256
ID  - ref1
ER  -