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Acquisition of traffic flow density using multi-source data fusion

机译:使用多源数据融合采集交通流量密度

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Traffic flow density is one of the most important parameters in traffic flow theory. It provides basic data for urban traffic management and control. However, it is highly difficult to directly collect real-time traffic flow density. The existing methods are simple in form, which are not suitable for complex traffic situations. The main purpose of this paper is to studying acquisition method of real-time traffic flow density by fusing Floating Car Data (FCD) and geomagnetic detection data. Least Squares Support Vector Regression (LS-SVR), which has properties such as global convergence and strong generalization capacity, is introduced to accomplish multi-source data fusion. The experimental result indicated that our approach has higher estimation accuracy than the traditional models.
机译:交通流量密度是交通流理论中最重要的参数之一。它为城市交通管理和控制提供了基本数据。但是,很难直接收集实时交通流量密度。现有方法以形式简单,其不适合复杂的交通情况。本文的主要目的是通过融合浮动汽车数据(FCD)和地磁检测数据来研究实时交通流量密度的采集方法。引入最小二乘支持向量回归(LS-SVR)具有诸如全球收敛性和强大的泛化容量的属性,以实现多源数据融合。实验结果表明,我们的方法具有比传统模型更高的估计精度。

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