# Evaluation of Construction Asphalt Pavements Based Toposable Set Theory: A Case Study
## 1 Introduction  
The purpose of asphalt pavement construction control is to ensure that the road has good quality. In the domestic context (China), control is currently achieved mainly in accordance with the Technical Specification for Highway Asphalt Pavement Construction (JTG F40-2004) [1] (hereinafter referred to as the construction specification) to guide and control the quality of asphalt pavement construction. The specification gives the degree of influence of each inspection item on the quality of the pavement, and the constructors are not aware of the influence of each inspection item on the control index, making the construction somewhat blind [2]. [PERSON] et al. showed through indoor tests and field investigations that non-uniformity (gradation segregation, temperature segregation and compaction segregation) has a large impact on the road performance of asphalt mixtures [3], while non-uniformity in asphalt pavements is mainly caused during the construction process. Therefore, to ensure the performance of asphalt pavements, the occurrence of non-uniformity in the asphalt mixture needs to be controlled during construction [4]. Abroad, in the 1950s, AASHTO recorded a large amount of asphalt pavement test data, which laid the foundation for later control techniques, as well as developing quality control specifications for raw materials and introducing the concept of statistics into quality control [5]. In the 1970s, the US applied statistical methods to pavement construction, used statistical methods to analyze variability in indicators, first proposed a QC/QA (quality control/quality assurance) system and established a complete quality control system forasphalt pavements in the 1980s. Since the 1990s, with the promotion of SHRP results, QC/QA systems have been widely used and have achieved better results in practical applications. In addition, there are more studies abroad on the influencing factors of pavement performance. The Mechanistic Empirical Pavement Design Guideline (MEPDG) method [6] in the USA predicts a rutting model for asphalt pavements that considers the mechanical response of the pavement structure and the performance of the asphalt mixture. The US NCHRP 9-22 report [7] analyzed the effects of factors including construction-related factors on fatigue cracking, rutting and low temperature cracking. More research has been carried out on prediction models such as cracking and rutting [8; 9], e.g., rutting prediction models can be categorized as empirical, theoretical and mechanistic-empirical models [10; 11]. [PERSON] et al. [12] predicted the Flow Number of asphalt mixes based on machine learning methods using parameters such as asphalt dosage, coarse aggregate ratio, filler ratio, mineral gap ratio and void ratio. The construction of asphalt pavements is a complex process in which materials, processes, personnel and equipment all have an impact on the quality of the asphalt pavement, and when coupled with adverse conditions such as environmental conditions, traffic load and tire tension, it will cause irreversible deformation of asphalt pavement, which will affect the service life of asphalt pavement [13; 14; 15]. There are many discussions on the control of asphalt pavement construction process, but most of them can be summarized into the following categories: first, analyze the construction control indicators, select or improve the construction indicators in the specification, and control the construction process of asphalt pavement through statistical control charts; secondly, analyze the variability of construction control indicators, get the variation range of indicators through experiment or simulation verification, and then dynamically control the pavement construction process through statistical control principle; thirdly, through the analysis of statistical control, select or recommend more convenient or appropriate quality control chart, and then carry out dynamic control of asphalt pavement construction process.