## 3 Results  
### Pavement Roughness and Noise  
Before the statistical analysis, the measurement data of pavement roughness must be revised to eliminate the obvious systematic errors such as the effect of concrete pavement joints. Then Origin Pro 8.5 was used to perform a regression analysis between the international roughness index (IRI) and the tire pavement noise level. The statistical results are shown in Figure 3.  
Figure 1: Test methods of concrete pavement texture.  
Figure 2: The on-board sound intensity system (OBSI).  
Figure 3 shows that there is a quadratic relation between the concrete pavement roughness and the noise level, and the correlation coefficient (\(R^{2}\)) is 0.74. It is indicated that there exists a certain correlation between the pavement roughness and tire/pavement noise of concrete pavement. To further investigate this relationship, Statistical Program for Social Sciences (SPSS) 19.0 statistical analysis softwarewas used for the correlation analysis of test samples. Table 2 presents the results of SPSS correlation analysis of descriptive statistics.  
As can be seen from Table 2, the average IRI and OBSI values of the samples are 1.73 m/km and 103.1 dB(A), respectively, and the standard deviations of the two variables are relatively small. This indicates a small discrete degree among various samples, which to some extent reflects the accuracy of the test data.  
Pearson correlation coefficient and \(p\)-value from the T statistics test were calculated through the SPSS correlation matrix analysis process. The results are shown in Table 3.  
Table 3 shows that the Pearson correlation coefficients of two variables are 1.0 and 0.82, respectively. This indicates that there is a strong correlation between the roughness and noise of concrete pavement. Indeed, a positive correlation between the concrete pavement roughness and tire/pavement noise can be observed. In other words, using the same test section the corresponding tire/pavement noise level  
\begin{table}
\begin{tabular}{c c c c} \hline  & **Sample Mean** & **Standard Deviation** & **N** \\ \hline IRI (m/km) & 1.73 & 0.675 & 35 \\ OBSI (dB(A)) & 103.1 & 1.366 & 35 \\ \hline \end{tabular}
\end{table}
Table 2: Statistical description of international roughness index (IRI) and On-Board Sound Intensity System (OBSI).  
Figure 3: Regression analyses between groove concrete pavement roughness and tire/road noise.  
\begin{table}
\begin{tabular}{c c c} \hline  & **Statistical Test Parameters** & **IRI (m/km)** & **OBSI (dB(A))** \\ \hline  & Pearson correlation coefficient & 1.0 & 0.82 ** \\  & Significant (bilateral) & & 0.0 \\ IRI (m/km) & Sum of squared & 16 & 26 \\  & Covariance & 0.46 & 0.76 \\  & N & 35 & 35 \\ \hline \end{tabular}
\end{table}
Table 3: Correlation analysis between pavement roughness and tire/pavement noise.  
also increases when increasing the international roughness index (IRI). What needs to be noticed is that when the IRI increases over 2.4 m/km, the noise level does not increase any more. The reason is that the fast scroll wheels make contact with the uneven concrete pavement surface, which can generate vibrational noise during the high-speed driving. The worse the roughness of concrete pavement, the higher the corresponding vibration noise will be [18].