为了从原始数据层面保证动态交通数据的质量,针对多检测器异步采样中非等采样率同时采样的情况,首先构建快速路多检测器动态系统,并对多检测器动态系统进行小波变换,提出基于小波和卡尔曼滤波的多尺度交通数据融合方法.最后,采用上海市南北高架快速路实测数据进行实验验证和对比分析.实验结果表明:对于添加噪声强度为2.5%、5.0%、7.5%和10.0%随机噪声的观测数据,该方法的数据融合效果均优于对比方法.%In order to guarantee the quality of dynamic traffic data on the original data level, by simultaneous sampling with different sampling rates, the multi-detector dynamic system of urban expressway was constructed and the multi-detector dynamic system was analyzed by using wavelet transform. Then, the multi-scale traffic data fusion method based on wavelet transform and Kalman filter was proposed. Finally, validation and comparative analysis were carried out by using actual data measured from the north-south viaduct in Shanghai. Experiment results indicate that when the stochastic noise intensity is 2. 5%, 5. 0%, 7. 5% and 10. 0% respectively, the data fusion effects of the proposed method are superior to that of the compared methods.
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