แบบจำลองประมาณปริมาณงานบำรุงปกติผิวทาง

Abstract

The annual budget consideration for road routine maintenance at present is mainly based on length of roads. As a result, the allocated budget may be insufficient or inappropriate for maintenance needs in each area. This paper presents a model for estimating work quantities of pavement routine maintenance including skin patching and deep patching. The study is based on data from the Department of Rural Roads. It is found that factors that are statistically correlated with work quantities of pavement patching are pavement service life, volume of heavy truck, average annual daily traffic (AADT), and type of structure. In addition, rainfall is not statistically correlated with skin patching quantity, but correlated with deep patching quantity when the road is in-service more than 7 years. The estimation models are developed into two types. One uses heavy truck data which is appropriate for high volume of truck roads or more than 100 trucks per day. Another type of model relies on AADT data instead which is appropriate for low volume of truck road. Moreover, the models are categorized into 3 groups based on their service lives: less than 3 years, between 3 – 7 years, and more than 7 years.  The objective of this research is to propose quantifying models for pavement routine maintenance according to each geographic, road usage, and road condition in order to planning routine maintenance budget efficiently.