DocumentCode :
2366186
Title :
Multi-phase time series models for motorway flow forecasting
Author :
Davarynejad, Mohsen ; Wang, Yubin ; Vrancken, Jos ; Van den Berg, Jan
Author_Institution :
Syst. Eng. Group, Delft Univ. of Technol., Delft, Netherlands
fYear :
2011
fDate :
5-7 Oct. 2011
Firstpage :
2033
Lastpage :
2038
Abstract :
In this study, a multi-phase time series prediction approaches is proposed for solving the motorway flow forecasting problem. The schemes presented here is based on an extensive study of flow patterns that were collected from a densely used ring road of Amsterdam, The Netherlands. The new prediction approach proposed here is based on a multiphase information extraction whose ultimate goal is to forecast traffic states at the boundary points of a network. With its simple architecture that makes the proposed approach of interest of practical application, a significant improvement is achieved in comparison with existing models. In its general form, the proposed approach could handle the curse of dimensionality, a common problem associated with the number of dimensions of input space.
Keywords :
automated highways; forecasting theory; knowledge acquisition; road traffic control; roads; time series; curse of dimensionality; flow pattern study; motorway flow forecasting; multiphase information extraction; multiphase time series model; multiphase time series prediction approach; prediction approach; traffic state forecasting; Adaptation models; Data models; Prediction algorithms; Predictive models; Roads; Support vector machines; Time series analysis; Adaptive Prediction; Demand Forecasting; Kalman Filter; Multi-phase Time Series Prediction; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on
Conference_Location :
Washington, DC
ISSN :
2153-0009
Print_ISBN :
978-1-4577-2198-4
Type :
conf
DOI :
10.1109/ITSC.2011.6082839
Filename :
6082839
Link To Document :
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