DocumentCode :
1939876
Title :
A short-term freeway traffic flow prediction method based on road section traffic flow structure pattern
Author :
Zhang, Ping ; Xie, Kunqing ; Song, Guojie
Author_Institution :
Key Lab. of Machine Perception (Minister of Educ.), Peking Univ., Beijing, China
fYear :
2012
fDate :
16-19 Sept. 2012
Firstpage :
534
Lastpage :
539
Abstract :
Accurate short-term traffic flow prediction is the foundation of the efficient and proactive management of freeway networks, especially on the abnormal traffic states. The relationship between traffic flow on the current section and the upstream stations can be used for predicting short-term traffic flow. In this paper, we reveal this relationship by the traffic flow structure pattern. The structure pattern can be drawn from real freeway toll data and a few video detective cameras on the freeway segments. Based on the stability pattern, a new traffic flow prediction algorithm has been proposed. Experimental based on real data showed that the prediction method based on structure pattern is an effective approach for traffic flow prediction, especially on the abnormal traffic state.
Keywords :
prediction theory; road traffic; transportation; abnormal traffic states; freeway network management; freeway segments; real freeway toll data; road section traffic flow structure pattern; short-term freeway traffic flow prediction method; stability pattern; traffic flow structure pattern; video detective cameras; Accuracy; History; Prediction algorithms; Prediction methods; Roads; Stability analysis; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
Conference_Location :
Anchorage, AK
ISSN :
2153-0009
Print_ISBN :
978-1-4673-3064-0
Electronic_ISBN :
2153-0009
Type :
conf
DOI :
10.1109/ITSC.2012.6338674
Filename :
6338674
Link To Document :
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