【摘要】：為了從原始數據層面保證動態(tài)交通數據的質量,針對多檢測器異步采樣中非等采樣率同時采樣的情況,首先構建快速路多檢測器動態(tài)系統(tǒng),并對多檢測器動態(tài)系統(tǒng)進行小波變換,提出基于小波和卡爾曼濾波的多尺度交通數據融合方法.最后,采用上海市南北高架快速路實測數據進行實驗驗證和對比分析.實驗結果表明:對于添加噪聲強度為2.5%、5.0%、7.5%和10.0%隨機噪聲的觀測數據,該方法的數據融合效果均優(yōu)于對比方法.
[Abstract]:In order to guarantee the quality of dynamic traffic data from the original data level, aiming at the case of asynchronous sampling of non-equal sampling rate with multiple detectors at the same time, an expressway multi-detector dynamic system is constructed. A multi-scale traffic data fusion method based on wavelet and Kalman filter is proposed. Finally, the experimental verification and comparative analysis are carried out by using the measured data of Shanghai North and South Expressway. The experimental results show that the data fusion effect of this method is better than that of the contrast method for the observation data with a noise intensity of 2.5% and 10.0% random noise.
【作者單位】： 青島理工大學汽車與交通學院;吉林大學交通學院;
【基金】：“十二五”國家科技支撐計劃資助項目(2014BAG03B03)
【分類號】：TP202;U491

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本文編號：2391559