NDLI: Urban expressway traffic state forecasting based on multimode maximum entropy model

Content Provider	Springer Nature Link
Author	Sun, XiaoLiang Jia, LiMin Dong, HongHui Qin, Yong Guo, Min
Copyright Year	2010
Abstract	The accurate and timely traffic state prediction has become increasingly important for the traffic participants, especially for the traffic managements. In this paper, the traffic state is described by Micro-LOS, and a direct prediction method is introduced. The development of the proposed method is based on Maximum Entropy (ME) models trained for multiple modes. In the Multimode Maximum Entropy (MME) framework, the different features like temporal and spatial features of traffic systems, regional traffic state are integrated simultaneously, and the different state behaviors based on 14 traffic modes defined by average speed according to the date-time division are also dealt with. The experiments based on the real data in Beijing expressway prove that the MME models outperforms the already existing model in both effectiveness and robustness.
Starting Page	2808
Ending Page	2816
Page Count	9
File Format	PDF
ISSN	16747321
Journal	Science in China Series E: Technological Sciences
Volume Number	53
Issue Number	10
e-ISSN	1862281X
Language	English
Publisher	SP Science China Press
Publisher Date	2010-09-02
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	traffic state forecast maximum entropy model multimode Engineering
Content Type	Text
Resource Type	Article
Subject	Engineering Materials Science

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Urban expressway traffic state forecasting based on multimode maximum entropy model