基于城市交通网络的交通流预测

2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE) Pub Date : 2016-08-01 DOI:10.1109/ICITE.2016.7581322

Dingsu Wang, Qi Zhang, Shunyao Wu, Xinmin Li, Ruixue Wang

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引用次数: 11

摘要

交通流预测已成为智能交通系统研究的热点。本文提出了一种新的交通流预测方法。我们根据交通流的双峰分布将24小时划分为4个阶段，并将城市交通网络的拓扑特征整合到4种典型的机器学习方法中。秦皇岛市的交通流实验验证了该方法的有效性和潜力。

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Traffic flow forecast with urban transport network

Traffic flow prediction has become a hot spot in the intelligent transportation system study. In this paper, novel methods are proposed to predict traffic flow. We divide 24 hours into 4 stages according to the bimodal distribution of traffic flow, and integrate topology features of urban traffic network into 4 typical machine learning methods. Experiments on the traffic flow of Qinhuangdao city demonstrate the effectiveness and potential of the proposed methods.

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2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)

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