基于重型载货汽车动态数据的区域公路货运量统计修正方法

Statistical Correction Method of Regional Highway Freight Volume Based on the Dynamic Data of Heavy Truck

为提高公路货运量统计的准确性,以重型载货汽车动态数据为基础,选取货车活跃数指标构建与公路货运量的回归模型并进行比较分析,选取平均相对误差最低的线性回归模型作为全国公路货运量的预测模型。基于华北、华东、中南三个区域共17个省(市)数据建立区域重型载货汽车活跃数与区域公路货运量之间的线性回归模型,判断以“车籍注册地”为原则统计的公路货运量与货车实际运行数据的区别。结果表明上海、北京、天津三地货车异地运营率较高,浙江、山东、江苏、湖南等地货车异地运营率较低。

In order to improve the accuracy of highway freight volume statistics,based on the dynamic data of heavy trucks,the regression model is established to analyze the relationship between the active number of heavy trucks and road freight volume.The linear regression model with the lowest average relative error is selected as the prediction model of highway freight volume nationwide.On this basis,17 provinces(cities)in North China,East China and Central South China are selected to establish a linear regression model between the active number of regional heavy trucks and the regional highway freight volume,and judge the difference between the highway freight volume based on the principle of"vehicle registration place"and the actual freight transport data.The results show that in Shanghai,Beijing and Tianjin,the heavy truck have a high nonlocal operation rate;in Zhejiang,Shandong,Jiangsu and Hunan province,the non-local operation rate is low.