TY - GEN
T1 - Travel time prediction by weighted fusion of probing vehicles and vehicle detectors data sources
AU - Hwang, Kevin P.
AU - Lee, Wei Hsun
AU - Wu, Wen Bin
PY - 2012
Y1 - 2012
N2 - Travel time information plays an important role in ITS, especially in advanced traveler information system (ATIS). Traditionally, travel time is predicted by a single data source, such as vehicle detectors (VD) or probing vehicles (PV). In this paper, we try to predict travel time by integrating these two data sources by a dynamic weighted fusion scheme. The weights of the data sources are dynamically determined by the distance weight scheme to enhance the prediction precision. The proposed TTP model is applied to a small traffic network located in the east and north district of Tainan City, Taiwan. VD data is provided by traffic bureau of Tainan city government and probing vehicles raw data is collected from a Taxi dispatching system. The experiment results show that dynamic weighted combination of these two data sources can enhance the precision of the TTP, and the prediction stability of the proposed model is better than both the single source TTP models (VD or PV).
AB - Travel time information plays an important role in ITS, especially in advanced traveler information system (ATIS). Traditionally, travel time is predicted by a single data source, such as vehicle detectors (VD) or probing vehicles (PV). In this paper, we try to predict travel time by integrating these two data sources by a dynamic weighted fusion scheme. The weights of the data sources are dynamically determined by the distance weight scheme to enhance the prediction precision. The proposed TTP model is applied to a small traffic network located in the east and north district of Tainan City, Taiwan. VD data is provided by traffic bureau of Tainan city government and probing vehicles raw data is collected from a Taxi dispatching system. The experiment results show that dynamic weighted combination of these two data sources can enhance the precision of the TTP, and the prediction stability of the proposed model is better than both the single source TTP models (VD or PV).
UR - http://www.scopus.com/inward/record.url?scp=84874462709&partnerID=8YFLogxK
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U2 - 10.1109/ITST.2012.6425224
DO - 10.1109/ITST.2012.6425224
M3 - Conference contribution
AN - SCOPUS:84874462709
SN - 9781467330701
T3 - 2012 12th International Conference on ITS Telecommunications, ITST 2012
SP - 476
EP - 481
BT - 2012 12th International Conference on ITS Telecommunications, ITST 2012
T2 - 2012 12th International Conference on ITS Telecommunications, ITST 2012
Y2 - 5 November 2012 through 8 November 2012
ER -