为提升关联交叉口群信号控制的性能,针对关联交叉口群各交叉口关联性强的特点,采用小波变换对关联交叉口群各进、出口的交通检测流量数据进行分解、降噪、重构,并利用系统聚类方法识别关联交叉口群的关键路径;最后应用南京市广州路某交叉口群的实测数据对模型的可靠性进行了检验。结果表明:该模型识别的交叉口群关键路径与实际情况相符;该关键路径识别方法受外界干扰小,适用于各种交通状态,拥有较高的运算效率和可靠性,可作为关联交叉口群信号控制优化的基础。
Abstract
In order to improve the traffic signal control performance, according to the strong relevance of the intersections at related intersections group, wavelet transform was applied to decomposition, noise reduction and reconstruction in a set of traffic flow time series collected from several detectors in signalized related intersections group. Critical route can be acquired by applying hierarchical cluster method to the reconstructed traffic count profiles. Field data of related intersections group at Guangzhou Road in Nanjing were used to verify reliability of model. The critical route identified by the proposed model which agrees well with actual state can be used for optimization of the traffic signal control for related intersections group with high efficiency, robustness and reliability. The proposed critical route identification method is little influenced by outside and can be regarded as basis of optimal control of related intersection group signal.
关键词
交通工程 /
交叉口群 /
小波变换 /
关键路径识别 /
数据挖掘
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Key words
traffic engineering /
intersection group /
wavelet transform /
critical route identifi-cation /
data mining
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中图分类号:
U491.23
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参考文献
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脚注
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基金
国家自然科学基金项目(50422283);江苏省建设科技发展计划项目(JS200603)
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