城市路网交通状态的改进Kriging估计方法

Kriging Based on Approximate Road Network Distance for Urban Traffic State Estimation

  • 摘要: 在非线性降维算法Isomap的基础上进行了改进,提出了一种基于度量多维标定法的空间变换方法。将原始网络空间中的路网距离转换为新欧氏空间中的近似路网距离,并在此距离度量基础上实现Kriging方法。通过对南昌市真实数据进行交通状态估计的实验发现,该方法比现有的基于欧氏距离度量的Kriging方法具有更高的估计精度,能够有效地解决交通领域中大规模路网交通运行状态监控的问题。

     

    Abstract: This paper improves Isomap algorithm,which is a nonlinear dimensionality reduction algorithm,and proposes a spatial alternation method based on metric multidimensional scaling.This method transforms road network distance in the original network space into approximate road network distance in a new Euclidean space,and then achieves Kriging based on this distance metric.The experiment of Nanchang's real data shows: this method has higher estimation accurate than Kriging based on Euclidean distance metric.Therefore,it is an effective solution to the problem of large-scale-road-network-level traffic state monitor.

     

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