宏观标定方法在Wiedemann驾驶行为阈值研究中的应用

发布时间：2018-06-10 05:39

  本文选题：交通工程 + 驾驶行为阈值　； 参考：《公路交通科技》2014年09期

【摘要】：基于流量速度图对Wiedemann74模型参数标定的宏观方法进行了研究,建立了集成VISSIM、Matlab、ExcelVBA的参数标定平台,以最小化流量速度图的实测值与仿真值的差异为优化目标,应用图像识别方法判别图像的差异性,利用遗传算法优化参数值,实现了参数自动寻优的迭代过程。建立的参数标定平台能够利用流量、速度等宏观运行数据标定驾驶行为阈值参数,为利用检测器数据实现自动化标定提供了有效手段,为分析驾驶行为特点提供了方法,解决了VISSIM软件中默认参数不适合我国交通状况导致仿真精度不高的问题。利用路侧激光检测器采集长沙市南二环路断面交通数据,根据标定后的参数、实测数据对Wiedemann模型的驾驶行为阈值曲线进行了拟合,根据驾驶行为分区对长沙市南二环路的驾驶行为进行了分析。
[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.
【作者单位】： 长沙理工大学交通运输工程学院;
【基金】：国家自然科学基金项目(71071024) 湖南省自然科学基金项目(12JJ2025) 长沙市科技局重点项目(K1106004-11)
【分类号】：U495;U491
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本文编号：2002159