## 1 Introduction
The second is the empirical method [19], which directly uses the observation data accumulated over several years to establish the regression relationship between the rutting amount and the relevant influencing variables through statistical analysis. Considering the actual conditions of test sections or field roads and laboratory tests, this method establishes an empirical equation for predicting the relationship between the permanent strain of the asphalt mixture layer and the properties of load and material. Finally, the rutting of the asphalt pavement under long-term repeated loads is determined. For example, [PERSON] et al. [20] used data collected from 930 test points in 39 test road sections in Michigan from 1991 to 1997, and established a rutting prediction model through structure analysis and nonlinear regression analysis, which took into account the correlation between the amount of rutting and the pavement structure, material parameters, and axle loads. Based on the laboratory asphalt pavement analyzer (APA) test, [PERSON] et al. [21] extended to APA test prediction research under different temperatures and axis loads. Through a large number of experiments, [PERSON] et al. [22; 23] obtained an empirical method for rutting prediction; that is, the relationship between rutting and influencing factors. [PERSON] et al. [24] established a double-logarithmic model of the relationship between permanent strain and cumulative axis loads. [PERSON] [25] conducted regression analysis on the data through a laboratory loop test, and established an empirical model including the thickness of the asphalt layer and the cumulative axis loads. Because the second method is limited by observation objects and regional conditions, the model is less applicable. Therefore, the first method is mainly used in the design of asphalt pavement in many countries to establish a rutting performance prediction model. For the prediction model of rutting performance established by the first method, due to the natural environment and loads that the actual pavement structure bears, there are certain differences from the test conditions imposed in the laboratory. It is necessary to continuously accumulate actual observation data during the service process to make periodic corrections and improvements to the established prediction model [26; 27; 28; 29; 30; 31; 32; 33]. Taking the American MEPDG as an example, the first edition of the guide [1] was officially promulgated in 2008, and the rutting prediction model was established based on the observation data and research results at that time. Afterwards, in the process of using this guide, in order to improve the accuracy and reliability of the rutting model, in the second edition of the guide [34] in 2015 and the third edition of the guide [35] in 2020, both of them have made a relatively large revision to the rutting prediction model. Although the model expression remains unchanged, the model parameters are adjusted greatly, and the prediction effect of the rutting performance prediction model after the correction has been greatly improved. The rutting model established by the first method is also used, as well as China's Specifications [3] promulgated in 2017. Due to the late promulgation of the specification, the asphalt pavement designed and opened to traffic in China in accordance with this specification has a longest service life of only 2 years. Due to the lack of long-term observation data of rutting in actual engineering, the effect of using the rutting prediction model is still unknown, and the model cannot be revised and improved periodically. Therefore, this research uses the long-term observation data of the RIGHTrack's full-scale pavement structures to carry out the accuracy analysis of the rutting performance prediction model in China's Specifications, and proposes a model correction method for the structure with poor model prediction to improve the reliability of the model, and make it more suitable for rutting prediction in the local region.