A Short-term Freeway Traffic Flow Prediction Method Based on Road Section Traffic Flow Structure Pattern

被引:0
|
作者
Zhang, Ping [1 ]
Xie, Kunqing [1 ]
Song, Guojie [1 ]
机构
[1] Peking Univ, Key Lab Machine Percept Minister Educ, Beijing 100871, Peoples R China
关键词
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暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
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收藏
页码:534 / 539
页数:6
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