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基于交通轨迹数据挖掘的道路限速信息识别方法

, PP. 118-126

Keywords: 道路限速,轨迹数据挖掘,浮动车数据,交通流,地图匹配,K近邻算法

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Abstract:

分析了道路限速信息的时空变化性,提出一种基于轨迹数据挖掘技术的道路限速信息自动识别方法。为了实现海量交通轨迹数据的快速处理,研究了快速地图匹配与数据清洗等预处理算法,分析了交通轨迹数据的速度分布特性与最高车速限制指标。基于路段行车速度的统计特性,构建了道路特征向量模型,以快速提取海量轨迹数据的潜在特征信息。提出了多投票K近邻分类算法对数据特性进行训练与学习,以实现对道路限速信息的快速识别。以福州市交通路网及其浮动车轨迹数据构建试验样本集进行训练、学习与交叉验证试验。试验结果表明在训练过程中,当样本数量达到1200时,方法的识别准确率最高达到93%,在仅有150个小训练样本下,方法的识别准确率也达到75%;方法具有近线性的处理性能,处理1.0×106条道路的限速信息仅用时46ms。

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