發(fā)布時間：2018-06-10 05:39

  本文選題：交通工程 + 駕駛行為閾值��； 參考：《公路交通科技》2014年09期

【摘要】：基于流量速度圖對Wiedemann74模型參數(shù)標(biāo)定的宏觀方法進(jìn)行了研究,建立了集成VISSIM、Matlab、ExcelVBA的參數(shù)標(biāo)定平臺,以最小化流量速度圖的實測值與仿真值的差異為優(yōu)化目標(biāo),應(yīng)用圖像識別方法判別圖像的差異性,利用遺傳算法優(yōu)化參數(shù)值,實現(xiàn)了參數(shù)自動尋優(yōu)的迭代過程。建立的參數(shù)標(biāo)定平臺能夠利用流量、速度等宏觀運(yùn)行數(shù)據(jù)標(biāo)定駕駛行為閾值參數(shù),為利用檢測器數(shù)據(jù)實現(xiàn)自動化標(biāo)定提供了有效手段,為分析駕駛行為特點(diǎn)提供了方法,解決了VISSIM軟件中默認(rèn)參數(shù)不適合我國交通狀況導(dǎo)致仿真精度不高的問題。利用路側(cè)激光檢測器采集長沙市南二環(huán)路斷面交通數(shù)據(jù),根據(jù)標(biāo)定后的參數(shù)、實測數(shù)據(jù)對Wiedemann模型的駕駛行為閾值曲線進(jìn)行了擬合,根據(jù)駕駛行為分區(qū)對長沙市南二環(huán)路的駕駛行為進(jìn)行了分析。
[Abstract]:Based on the flow velocity diagram, the macroscopic method of Wiedemann74 model parameter calibration is studied, and a parameter calibration platform of integrated Vissimo Matlab Excel VBA is established. The optimization goal is to minimize the difference between the measured value and the simulation value of the flow velocity diagram. The image recognition method is used to distinguish the difference of the image and the genetic algorithm is used to optimize the parameter value to realize the iterative process of automatic parameter optimization. The established calibration platform can calibrate the threshold parameters of driving behavior using macroscopic operation data, such as flow rate and speed, which provides an effective means for automatic calibration by using detector data, and provides a method for analyzing the characteristics of driving behavior. It solves the problem that the default parameters in Visual IM software are not suitable for traffic conditions in our country and the simulation accuracy is not high. The road side laser detector is used to collect the traffic data of the second ring road in Changsha. The driving threshold curve of Wiedemann model is fitted according to the calibrated parameters and the measured data. The driving behavior of Nanshan second Ring Road in Changsha City was analyzed according to driving behavior zoning.
【作者單位】： 長沙理工大學(xué)交通運(yùn)輸工程學(xué)院;
【基金】：國家自然科學(xué)基金項目(71071024) 湖南省自然科學(xué)基金項目(12JJ2025) 長沙市科技局重點(diǎn)項目(K1106004-11)
【分類號】：U495;U491
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本文編號：2002159