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高速公路路面小修保养费用影响因素量化分析
引用本文:史小丽,李玉环,张明,张平.高速公路路面小修保养费用影响因素量化分析[J].同济大学学报(自然科学版),2019,47(9):1302-1309.
作者姓名:史小丽  李玉环  张明  张平
作者单位:长安大学 公路学院, 陕西 西安 710064,长安大学 公路学院, 陕西 西安 710064,长安大学 公路学院, 陕西 西安 710064,陕西省交通建设集团公司, 陕西 西安 710075
基金项目:陕西省交通运输厅科技项目(16-34k)、中央高校基本科研业务费资助项目(300102218112)
摘    要:为提高高速公路路面小修保养费用决策水平,采用阶层回归分析方法,进行小修保养费用影响因素量化研究.通过定性分析将影响因素界定为地区因素、通车年限、特大桥梁比例、长与特长隧道比例和交通因素,其中交通因素分为5种情况;通过对变量进行预处理,基于16条高速公路的历史数据进行量化研究.结果表明,在控制地区变量的条件下,各区组对模型的整体解释力均较显著,其中通车年限的增量解释力和在各区组的统计意义最为显著;同等条件下特大桥比例的标准化回归系数(β系数)远大于长与特长隧道比例的β系数,AADT(annual average daily traffic)和重车流量区组的β系数较其他交通因素区组的数值大.因此,路面资产小修保养费用受到地区因素、通车年限、大于1 000 m的桥梁比例、AADT和重车流量的影响.

关 键 词:道路工程  路面资产  小修保养费用  阶层回归分析  影响因素
收稿时间:2018/10/26 0:00:00
修稿时间:2019/7/12 0:00:00

Quantitative Analysis of Influencing Factors on Pavement Routine Maintenance Cost of Expressway
SHI Xiaoli,LI Yuhuan,ZHANG Ming and ZHANG Ping.Quantitative Analysis of Influencing Factors on Pavement Routine Maintenance Cost of Expressway[J].Journal of Tongji University(Natural Science),2019,47(9):1302-1309.
Authors:SHI Xiaoli  LI Yuhuan  ZHANG Ming and ZHANG Ping
Abstract:In order to improve the decision level of pavement routine maintenance expenditure of expressway, hierarchical regression analysis method was used to quantify the influencing factors of routine maintenance cost. The influencing factors were defined as regional factors, ages, extra-large bridges ratio, long and extra-long tunnel ratio, and traffic factors which were divided into five cases. The quantitative research was carried out based on the historic data of 16 highway pavement assets after the variables were pretreated. The results show that the overall explanatory power of each group to the model is remarkable under the condition of controlling regional variables; the incremental explanatory power and the statistical significance in each group of the age are the most remarkable; the normalized regression coefficient (beta coefficient) of the extra bridge ratio is larger than the long and extra-long tunnel ratio under the same conditions ; and the beta coefficient of the AADT (annual average daily traffic) and heavy traffic flow are greater than other traffic groups. Thus, the calculation of pavement assets routine maintenance cost is affected by regional factors, the age, the extra bridges ratio, AADT and heavy traffic flow.
Keywords:road engineering  pavement assets  routine maintenance costs  hierarchical regression analysis  influencing factors
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