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以交通混合程度最高的单幅路为研究对象,在大量实测数据基础上,采用多因素方差分析法检验了本向机动车流量、对向机动车流量、本向非机动车流量、行人横向干扰程度对车流速度产生的影响。由美国联邦公路局BPR函数模型拓展得到混合交通条件下机动车路阻函数的通用形式,基于统计学原理对实测数据进行变量筛选和参数标定,建立了综合考虑机非干扰、对向干扰和横向干扰的实用路阻函数模型。结果表明:在理论分析基础上,由试验数据标定得到的BPR改进模型优于纯粹由数据拟合得到的线性回归模型。
Based on a large number of measured data, a multi-factor analysis of variance (ANOVA) was used to test the traffic flow to the motor vehicle, the flow to the motor vehicle, the current non-motorized traffic, the horizontal disturbance of pedestrians The impact of degree on traffic speed. The general form of the motor vehicle road resistance function under mixed traffic conditions is expanded by the BPR function model of the Federal Highway Administration. Based on the statistical principle, variable screening and parameter calibration are performed on the measured data, and a comprehensive consideration of non-interference, Interference Practical Road Resistance Function Model. The results show that on the basis of theoretical analysis, the BPR improved model calibrated by the experimental data is better than the linear regression model purely fitted by the data.