發(fā)布時(shí)間：2018-12-25 19:49

【摘要】：為了從原始數(shù)據(jù)層面保證動(dòng)態(tài)交通數(shù)據(jù)的質(zhì)量,針對(duì)多檢測(cè)器異步采樣中非等采樣率同時(shí)采樣的情況,首先構(gòu)建快速路多檢測(cè)器動(dòng)態(tài)系統(tǒng),并對(duì)多檢測(cè)器動(dòng)態(tài)系統(tǒng)進(jìn)行小波變換,提出基于小波和卡爾曼濾波的多尺度交通數(shù)據(jù)融合方法.最后,采用上海市南北高架快速路實(shí)測(cè)數(shù)據(jù)進(jìn)行實(shí)驗(yàn)驗(yàn)證和對(duì)比分析.實(shí)驗(yàn)結(jié)果表明:對(duì)于添加噪聲強(qiáng)度為2.5%、5.0%、7.5%和10.0%隨機(jī)噪聲的觀測(cè)數(shù)據(jù),該方法的數(shù)據(jù)融合效果均優(yōu)于對(duì)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(xué)汽車與交通學(xué)院;吉林大學(xué)交通學(xué)院;
【基金】：“十二五”國(guó)家科技支撐計(jì)劃資助項(xiàng)目(2014BAG03B03)
【分類號(hào)】：TP202;U491

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本文編號(hào)：2391559