發(fā)布時(shí)間：2018-03-29 23:30

  本文選題：多源交通信息　切入點(diǎn)：信息融合　出處：《計(jì)算機(jī)工程與應(yīng)用》2017年05期

【摘要】：針對(duì)單一檢測(cè)器所得到的交通數(shù)據(jù)不能夠全面準(zhǔn)確地反映實(shí)際的交通狀態(tài),提出一種基于AF-SVR模型的城市快速路多源交通信息融合的方法。首先通過(guò)將相同路段中不同檢測(cè)器的速度數(shù)據(jù)作為學(xué)習(xí)樣本輸入到支持向量機(jī)回歸模型(Support Vector Regression,SVR)中進(jìn)行訓(xùn)練。然后利用魚群算法(Artificial Fish,AF)對(duì)支持向量機(jī)回歸模型中的參數(shù)進(jìn)行優(yōu)化,獲得最優(yōu)的信息融合模型,用于多源交通信息的融合,輸出為能準(zhǔn)確反映真實(shí)交通狀態(tài)的速度數(shù)據(jù),并用人工采集的速度數(shù)據(jù)作為真值進(jìn)行驗(yàn)證。最后將此方法應(yīng)用于成都市三環(huán)快速路路段上的多源交通信息融合,取得了令人滿意的結(jié)果。
[Abstract]:In view of the fact that the traffic data obtained by a single detector can not reflect the actual traffic state comprehensively and accurately, A method of multi-source traffic information fusion for urban expressway based on AF-SVR model is proposed. Firstly, the speed data of different detectors in the same section are input into support Vector regression model (SVM) as learning samples. Then the parameters in the regression model of support vector machine are optimized by using the fish swarm algorithm named artificial Fishery (AFF). The optimal information fusion model is obtained for multi-source traffic information fusion. The output is the speed data which can accurately reflect the real traffic state. Finally, the method is applied to the multi-source traffic information fusion on Chengdu Sanhuan Expressway, and satisfactory results are obtained.
【作者單位】： 西南交通大學(xué)交通運(yùn)輸與物流學(xué)院;四川省交通運(yùn)輸廳公路規(guī)劃勘察設(shè)計(jì)研究院;
【基金】：國(guó)家自然科學(xué)基金(No.51308475) 四川省科技支撐計(jì)劃資助項(xiàng)目(No.2011FZ0050)
【分類號(hào)】：U491;TP18

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