基于随机参数线性回归的交通流速度-密度关系模型研究

Research on Traffic Flow Speed-Density Model Based on Random-Parameter Linear Regression

为研究异质性条件下交通流速度-密度关系,本文基于随机参数线性回归建立随机交通流速度-密度关系基本图模型。利用随机参数线性回归对速度-密度关系进行参数拟合,并对随机模型进行参数检验和误差分析,计算结果表明,已提出的Greenshields、Greenberg、Underwood和Northwestern随机参数模型能反映交通流异质性对速度和密度关系的影响,且4个随机参数模型的平均绝对误差较对应的固定参数模型分别降低57.04%、81.30%、74.48%和52.27%。本研究提出的方法可以推广到不同的交通流速度-密度关系基本图模型,体现不同数据集的数据特征,在交通流理论中有非常重要的应用。

In order to study the traffic flow speed-density relationship under the condition of heterogeneity,the fundamental diagram model of speed-density relationship of stochastic traffic flow is established based on random-parameter linear regression.The random-parameter linear regression is used to fit the relationship between speed and density,and the random parameters are tested and the error of the model is analyzed.The calculation results show that the Greenshields,Greenberg,Underwood and Northwestern model with random parameter reflect the influence of traffic flow heterogeneity on the relationship between speed and density,and the average absolute errors of the four random parameter models is reduced by 57.04%,81.30%,74.48%,and 52.27% respectively,compared with the corresponding fixed parameter model.The proposed method can be extend to different fundamental diagram of traffic flow speed-density relationship,reflecting the characteristics of different datasets,and has an important application in traffic flow theory.