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从交通流扩散的特点和人的先验知识出发,提出采用Kriging插值法对路网中无检测器路段进行交通数据插补。基于交通数据空间相关性的特征,对交通数据进行空间建模,从而以空间距离作为度量基准对未知路段交通数据进行估计。利用南昌市浮动车系统中提取的路段行程速度作为试验数据,进行了试验验证。研究结果表明:在城市交通中各个典型时段行程速度的插补值标准差可以控制在8 km·h-1以内;在针对路网形态差异较大的中心区和湖区分别进行的试验中,行程速度的平均绝对误差都保持在2~5 km·h-1之间。可见,该方法具有良好的时态和区域移植性。
Based on the characteristics of traffic flow diffusion and prior knowledge of human beings, Kriging interpolation method is proposed to interpolate the traffic data without detector in the road network. Based on the characteristics of the spatial correlation of traffic data, the traffic data is modeled in space, and the traffic data of unknown links are estimated based on the spatial distance. Based on the travel speed of the section extracted from the floating car system in Nanchang City, the test data are used to verify the test results. The results show that the standard deviation of the interpolated travel velocities can be controlled within 8 km · h-1 for the typical traffic hours in urban traffic. In the tests carried out separately for the central and lake areas with large differences in road network, The average absolute error of speed is maintained at 2 ~ 5 km · h-1. Can be seen that the method has good tense and regional portability.