基于路口转弯流量的OD估计方法研究
发布时间：2018-10-10 14:49
【摘要】：机动车起终点矩阵(Origin-Destination Matrix,OD矩阵)的估计是交通规划和交通管理等工作的重要基础.本文主要研究在采集数据日渐精细情况下的机动车OD估计方法.基于车牌识别数据提取出路口转弯流量和路段断面流量,在此基础上建立应用广义最小二乘模型进行机动车OD估计的模型及方法.利用S-Paramics仿真平台及实测数据,应用Nguyen Dupuis网络和实际城市路网对本文研究的方法进行了对比验证,分析对比验证了是否已知真实OD、不同的数据输入类型、不同的已知检测量的比例等.结果显示,与使用路段流量相比,使用转弯流量可以提高OD估计的准确性.
[Abstract]:The estimation of Origin-Destination Matrix,OD matrix is an important basis for traffic planning and traffic management. In this paper, the vehicle OD estimation method based on the increasingly fine data acquisition is studied. Based on the license plate recognition data, the turning flow and section flow are extracted, and the model and method of vehicle OD estimation based on the generalized least square model are established. Using S-Paramics simulation platform and measured data, Nguyen Dupuis network and actual urban road network are used to compare and verify the methods studied in this paper. The analysis and comparison verify whether different data input types of real OD, are known. Different proportions of known measurements, etc. The results show that turning flow can improve the accuracy of OD estimation.
【作者单位】： 清华大学交通研究所;清华大学恒隆房地产研究中心;廊坊市交通警察支队;
【基金】：国家自然科学基金项目(71361130015) 国家科技支撑计划课题(2014BAG03B03)
【分类号】：U491.1
[Abstract]:The estimation of Origin-Destination Matrix,OD matrix is an important basis for traffic planning and traffic management. In this paper, the vehicle OD estimation method based on the increasingly fine data acquisition is studied. Based on the license plate recognition data, the turning flow and section flow are extracted, and the model and method of vehicle OD estimation based on the generalized least square model are established. Using S-Paramics simulation platform and measured data, Nguyen Dupuis network and actual urban road network are used to compare and verify the methods studied in this paper. The analysis and comparison verify whether different data input types of real OD, are known. Different proportions of known measurements, etc. The results show that turning flow can improve the accuracy of OD estimation.
【作者单位】： 清华大学交通研究所;清华大学恒隆房地产研究中心;廊坊市交通警察支队;
【基金】：国家自然科学基金项目(71361130015) 国家科技支撑计划课题(2014BAG03B03)
【分类号】：U491.1
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