# Statistical Pass-By for Unattended Road Traffic Noise Measurement in an Urban Environment
## 5 Results
### Validation  
The validation phase was performed in V (Sesto Fiorentino), where a long, straight road section with a free field condition was available to correctly perform SPB measurement with a suitable sample for a daytime, attended section. The road was paved with a low-noise surface. The number of acquired events is reported in Table 7. A single night acquisition was needed for U-SPB analysis of light vehicles and two nights for the heavy \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Lane** & **No. of Events SPB-L** & **No. of Events U-SPB** \\ \hline Light & near & 114 & 129 \\  & far & 102 & 98 \\  & near & 13 & 15 \\  & far & 11 & 12 \\  & near & 10 & 15 \\  & far & 11 & 20 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Number of analyzed pass-bys in T1 (night dataset and SPB-L). Figure 6: U-SPB L\({}_{\text{Aeqh}}\) model and measured L\({}_{\text{Aeqh}}\) comparison in T1. and two wheeler categories. A further differentiation of heavy vehicles into two-axis and multi-axis vehicles is reported since it came out that such a distinction improved the result on this road. The identification of truck classes at the monitoring station was performed based on vehicle length, a procedure that can give some unfortunate mismatching. This further differentiation led us to consider a further category and to compare SPB-L with only two-axis trucks of U-SPB since the number of multi-axis vehicles in the SPB-L sample was lower. Table 8 shows the fit results according to Equation (2). The two methods' results were equivalent in terms of the A parameter, apart from the heavy vehicle category in the far lane. Some buses were included in the SPB sample that were not clearly identified in the U-SPB one. With all the information, it was possible to estimate the SPBI with Equation (3), calculating for a low-speed road, i.e., with a reference speed equal to 50 km/h, as reported in Table 9.  
SPBI values results were equivalent, with a less than 1 dB(A) difference, even if associated uncertainties were high due to the low number of heavy vehicle events. Thus, the procedure can also be considered as validated on a low-noise pavement. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Lane** & **No. of Events SPB-L** & **No. of Events U-SPB** \\ \hline \multirow{3}{*}{Light} & near & 65 & 120 \\  & far & 35 & 114 \\  & near & 13 & 31 \\  & far & 9 & 34 \\  & near & 8 two axes + 3 multiple axes & 12 two axes + 10 multiple axes \\  & far & 8 two axes & 13 two axes + 12 multiple axes \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Number of analyzed pass-bys in V. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Category** & **Lane** & **Parameter** & **Monitoring Station** & **Mic 1.2 m** \\ \hline \multirow{6}{*}{Light} & & \(a\pm da\) & 69.3 \(\pm\) 0.5 & 69.5 \(\pm\) 0.6 \\  & near & \(b\pm db\) & 17.7 \(\pm\) 4.0 & 14.7 \(\pm\) 9.3 \\  & & \(\chi^{2}\) & 1.2 & 0.5 \\  & & \(a\pm da\) & 68.5 \(\pm\) 0.4 & 69.0 \(\pm\) 0.8 \\  & far & \(b\pm db\) & 17.3 \(\pm\) 4.6 & 14.5 \(\pm\) 10.8 \\  & & \(\chi^{2}\) & 3.6 & 0.2 \\  & & \(a\pm da\) & 73.9 \(\pm\) 1.2 & 73.4 \(\pm\) 0.6 \\  & near & \(b\pm db\) & 8.7 \(\pm\) 10.9 & 9.3 \(\pm\) 4.6 \\  & & \(\chi^{2}\) & 0.2 & 40 \\  & & \(a\pm da\) & 74.5 \(\pm\) 0.8 & 73.5 \(\pm\) 0.9 \\  & far & \(b\pm db\) & 21.7 \(\pm\) 7.4 & 15.7 \(\pm\) 9.5 \\  & & \(\chi^{2}\) & 2.4 & 44 \\  & & \(a\pm da\) & 72.0 \(\pm\) 0.9 & 74.3 \(\pm\) 1.5 \\  & near & \(b\pm db\) & 11.5 \(\pm\) 10.3 & 9.3 \(\pm\) 4.6 \\  & & \(\chi^{2}\) & 108 & 183 \\  & & \(a\pm da\) & 70.6 \(\pm\) 1.0 & 73.5 \(\pm\) 0.9 \\  & far & \(b\pm db\) & 15.8 \(\pm\) 9.4 & 15.7 \(\pm\) 9.5 \\  & & \(\chi^{2}\) & 113 & 39 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: SEL fit comparison for night U-SPB and SPB-L in V. \(a\) and \(b\) units are dB(A).