## 6 Results and Discussion
### Correction of Asphalt Pavement Rutting Prediction Model  
To ensure the wide applicability of the rutting prediction model in China's Specifications and the model in MEPDG, the measured rutting data from actual projects and test tracks in different regions of the country were used in establishing the model. As a result, the applicability is ensured, but the prediction accuracy of the model is limited. As shown in [12], when \(R^{2}\) is higher than 0.60, the prediction effect of the model is acceptable and can be used for design. After verifying the rutting prediction models of different pavement structures based on the RIOHTrack measured results, the predicted value of only the rutting with Structure I is close to the measured value. The \(R^{2}\) of the rutting model can reach 0.60 and above, and the accuracy of other structures cannot reach the value. The reason for this phenomenon is that, on the one hand, the structure and material characteristics of some sections, such as rigid base structure and full-depth asphalt concrete layer structure, are not considered when the model is established, which leads to the poor prediction effect of the model on these structures. On the other hand, the RIOHTrack, which provides the measured data in this research, has certain differences from the model in climate and traffic environments. The rutting model can only be used with local correction. At present, in terms of the rutting model, the commonly used correction method aims to introduce a local correction coefficient based on the existing model expression to improve the model, thereby improving the prediction accuracy. In [26; 27; 28; 29; 30; 31; 32; 33], the local correction is carried out for the rutting model in MEPDG. The main method is that three local correction coefficients, namely, \(\beta_{1}\), \(\beta_{2}\), and \(\beta_{3}\), are introduced to correct the constant term of the model, the exponential term of temperature, and the exponential term of cumulative ESALs, respectively. Subsequently, the model parameters are calibrated using the rutting observation results of local actual projects or test tracks. The rutting model in China's Specifications is similar to that in the MEPDG in its principles and expression. Therefore, this method can be used to make the local correction of the rutting model to establish a high-precision rutting model suitable for the region where the RIOHTrack is located. According to this idea, we propose a local correction method for the prediction model of the rutting performance of China's asphalt pavement, which is briefly described as follows:  
1. On the basis of the existing rutting performance prediction model Equation (3) in China, the local correction coefficients \(\beta_{1}\), \(\beta_{2}\), and \(\beta_{3}\) are introduced to improve a new rutting prediction model; see Equation (7). Among them, \(\beta_{1}\) is used to correct the constant term of the existing rutting model, \(\beta_{2}\) is used to correct the exponential term of the temperature, and \(\beta_{3}\) is used to correct the exponential term of the cumulative ESALs. 2. Relying on local projects and test sections, long-term observation of rutting deformation of asphalt pavement is carried out, and the measured rutting data with the cumulative ESALs are obtained. These data can reflect the long-term evolution of pavement rutting under the combined effect of multiple factors such as local climate environment, traffic load, pavement structure, and material type. 3. Based on the long-term observation results of rutting deformation, a new rutting prediction model after correction is used to fit the rutting data according to the least squares method, so the local correction coefficients \(\beta_{1}\), \(\beta_{2}\), and \(\beta_{3}\) can be obtained, and the model prediction errors are obtained to judge the model accuracy. Finally, taking these coefficients into Equation (7), the new rutting prediction model after local correction can be obtained.