DocumentCode :
2367307
Title :
Road Traffic State Prediction with a Maximum Entropy Method
Author :
Dong, Honghui ; Jia, Limin ; Sun, Xiaoliang ; Li, Chenxi ; Qin, Yong ; Guo, Min
Author_Institution :
State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
fYear :
2009
fDate :
25-27 Aug. 2009
Firstpage :
628
Lastpage :
630
Abstract :
The prediction of the traffic state can give the people the important traveling information. In this paper, the traffic state prediction problem is studied. A maximum entropy(ME) approach is proposed for the traffic state prediction, which consider the prediction process as a classification problem instead of predicting the traffic flow parameters. The traffic state is defined as six classes according to the level of service. The maximum entropy approach is introduced to model this prediction process. In the ME framework, more different features can be used regardless of the features´ dependence. The temporal and spatial features can be used together, which is hard to complished in the previous methods. The experiments show that the maximum entropy model is competent for the traffic state prediction. The most advantage of the maximum entropy model is that the road network features can be introduced. And this method can be also introduced to predict the long time traffic state in the future work.
Keywords :
maximum entropy methods; pattern classification; road traffic; classification problem; level of service prediction; maximum entropy method; road traffic prediction; road traffic state; Conference management; Entropy; Predictive models; Rail transportation; Railway safety; Road safety; Road transportation; Sun; Telecommunication traffic; Traffic control; Maximum Entropy; Traffic state; level of service;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5209-5
Electronic_ISBN :
978-0-7695-3769-6
Type :
conf
DOI :
10.1109/NCM.2009.411
Filename :
5331799
Link To Document :
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