## 6 Results and Discussion
### Evaluation on Asphalt Pavement Rutting Prediction Model
For STR17 with the smallest error, the MSE is 1.72 mm\({}^{2}\); the RMSE is 1.31 mm; the MAE is 1.15 mm; and the MAPE is 23.1%. The critical values (\(N_{e}\)\({}^{\prime}\)) of STR12, STR11, STR13, STR16, and STR17 are 35 million, 50 million, 30 million, 45 million, and 25 million, respectively. The \(R^{2}\) of five structural rutting models are 0.0860, 0.4220, 0.2500, 0.0444, and 0.2084. \(R^{2}\) is in the range of 0-0.5. The prediction effect is not ideal. From the meaning of the \(R^{2}\), although the rutting model can be used to predict these structures with \(R^{2}\) between 0 and 0.5, the accuracy is not high. The main reason is that the rutting observation data in this research are based on the RIGHTrack accelerated loading test. Compared with 10 highways and 5 test sections used for establishing the model in China's Specification, some differences are observed in the geographical location, climate environment, and traffic load, etc. A local correction coefficient should be introduced into the rutting model by referring to [26; 27; 28; 29; 30; 31; 32; 33], and the model must be modified to obtain a rutting prediction model suitable for the location of the RIGHTrack, thereby improving the accuracy of model prediction. According to the equivalence relationship between the design life and the cumulative ESALs in China's Specification, under the heavy traffic load level, the expressway with a 30-year design life is equivalent to more than 50 million cumulative ESALs of pavement. Table 3 summarizes the measured rutting values and model-predicted values of each pavement structure of the RIGHTrack under the cumulative 50 million ESALs in Figure 6. From the data in Table 3, it can be seen that, at the end of design life, the structures with the largest difference between the measured rutting values and the model predicted values are Structure II and VII, which are also predicted poorly in Table 2. Furthermore, STR7 and STR11 have the smallest difference between the measured rutting values and the model predicted values. However, from the rutting evolution curve in Figure 6, the rutting model has the highest prediction effect only when it reaches the end of design life. The prediction effect of the whole life cycle is not ideal, which is basically consistent with the results of the previous analysis. The aforementioned analysis results show that the rutting model in China's Specifications has significant structural dependence. Some problems are encountered in using a unified rutting model for the prediction of different structures, especially for rigid base and full-depth asphalt pavements. The rutting evolution process of the two structures is not considered when the model is established, so the prediction effect of the model on both structures is poor. To ensure the prediction accuracy of the rutting model, we should correct, improve, and optimize the established rutting model combined with the long-term \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline
**Structure** & **1** & **TR2** & **TR4** & **STR5** & **STR7** & **STR8** & **STR10** & **STR12** & **STR11** & **STR13** & **STR16** & **STR17** & **STR18** & **STR19** \\ \hline RIGHTrack & 7.70 & 7.89 & 5.15 & 6.40 & 9.99 & 11.60 & 10.69 & 8.90 & 10.05 & 8.50 & 7.89 & 6.63 & 10.45 & 7.36 \\ \hline Model & 9.20 & 9.19 & 9.69 & 9.87 & 9.91 & 9.85 & 9.57 & 9.28 & 10.02 & 9.91 & 8.25 & 8.86 & 15.72 & 11.96 \\ \hline MAPE (\%) & 19.5 & 16.5 & 88.1 & 54.2 & 0.8 & 15.1 & 10.5 & 4.3 & 0.4 & 16.6 & 4.5 & 33.8 & 50.5 & 62.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Rutting values at the end of design life. evolution data of rutting deformation of pavement structure with load and environment according to the characteristics of the pavement structures and materials in different areas, as well as the geographical location, climate environment, and traffic load, to improve the prediction accuracy. Finally, a high-precision rutting prediction model suitable for different pavement structures and areas is obtained.