## 7 Conclusions  
Based on the measured value of the rutting model with the pavement structure represented by the RIGHTrack full-scale test track, the rutting prediction model in China's Specifications is analyzed. Moreover, the following conclusions are drawn:  
1. The rutting model in China's Specifications for Design of Highway Asphalt Pavement has significant structural dependence. Different structures are predicted using a unified rutting model with different prediction accuracies.
2. The existing rutting model is used for prediction. Structure I has the highest accuracy and the smallest error, and the \(R^{2}\) is greater than 0.6. Rigid base and full-depth asphalt pavement structures have the worst accuracy, and the \(R^{2}\) is negative. The prediction accuracy of other structures is not high, and the \(R^{2}\) is in the range of 0-0.5.
3. To improve prediction accuracy, local correction coefficients are introduced in the existing rutting prediction model to establish a new one. The RIGHTrack rutting measured value is adopted to fit the new rutting prediction model, and the local correction coefficients of different structures are obtained.
4. After local correction, the accuracy of the rutting prediction model of all structures is greatly improved. The \(R^{2}\) values are greater than 0.87. The predicted values of the rutting models with these structures are relatively close to the measured values. The measured result fluctuates up and down near the prediction curve, the error of the model prediction declines, and the accuracy is improved significantly.
5. The measured rutting data in this research are the test results under the combined effect of local climate environment, traffic load, pavement structure, and material type. On the basis of this test data, the new rutting prediction model obtained after local correction will also have higher regional applicability, and is more suitable for rutting prediction of various pavement structures in the area where the RIGHTrack is located, and the accuracy is also higher.  
In this research, a local correction method of the rutting prediction model is proposed. Although this method is discussed for the rutting model in China's Specification, the basic principle of this method is to introduce correction coefficients. The constant terms, exponential terms of loads, and environment parameters in the model are modified respectively to improve the prediction accuracy of the model. The ideas and methods of this model correction also have a certain reference value for the correction of rutting models in other regions. When the accuracy of the estimation of the existing rutting models in other regions is poor, you can refer to this research's method to make local correction on key parameters to improve accuracy and enhance regional applicability. In addition, the RIGHTrack full-scale pavement test track, which this research is based on, is still carrying out accelerated loading tests. It is expected that by the end of 2022, cumulative ESALs will reach 65 million ESALs. The related work in this research will also carry out further tracking research and analysis with the update of long-term observation data of rutting.  
The authors confirm contribution to the paper as follows: conceptualization and methodology: X.Z.; data curation: Y.W. and Z.M.; formal analysis and validation: Y.W., X.Z. and X.W.; writing and visualization: Y.W., X.Z. and Z.M. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Key of Research and Development Plan under Grant number 2020 YFA0714300.