## 4 Results and Discussion
\begin{table}
\begin{tabular}{l c} \hline \hline
**Correlation between** & **r** \\ \hline \(\left[AVG\,of\,\,VG_{i}^{FS}-AVG\,of\,\,VG_{i}^{IS}\right]\) and \(\left[AVG\,of\,\,DG_{i}^{FS}-AVG\,of\,\,DG_{i}^{IS}\right]\) & \(-0.7559\) \\ \(AVG\,of\,\,VG_{i}^{FS}-AVG\,of\,\,VG_{i}^{IS}\) and \(\left[STD\,of\,\,VG_{i}^{FS}-STD\,of\,\,VG_{i}^{IS}\right]\) & \(-0.3195\) \\ \(AVG\,of\,\,VG_{i}^{FS}-AVG\,of\,\,VG_{i}^{IS}\) and \(\left[STD\,of\,\,DG_{i}^{FS}-STD\,of\,\,DG_{i}^{IS}\right]\) & \(-0.3777\) \\ \(AVG\,of\,\,VP_{i}^{FS}-AVG\,of\,\,VP_{i}^{IS}\) and \(\left[AVG\,of\,\,DP_{i}^{FS}-AVG\,of\,\,DP_{i}^{IS}\right]\) & \(-0.9445\) \\ \(AVG\,of\,\,VP_{i}^{FS}-AVG\,of\,\,VP_{i}^{IS}\) and \(\left[STD\,of\,VP_{i}^{FS}-STD\,of\,\,VP_{i}^{IS}\right]\) & \(-0.6123\) \\ \(AVG\,of\,\,VP_{i}^{FS}-AVG\,of\,\,VP_{i}^{IS}\) and \(\left[STD\,of\,\,DP_{i}^{FS}-STD\,of\,\,DP_{i}^{IS}\right]\) & \(-0.7009\) \\ \(AVG\,of\,\,DG_{i}^{FS}-AVG\,of\,\,DG_{i}^{IS}\) and \(\left[STD\,of\,\,VG_{i}^{FS}-STD\,of\,\,VG_{i}^{IS}\right]\) & \(0.4903\) \\ \(AVG\,of\,\,DG_{i}^{FS}-AVG\,of\,\,DG_{i}^{IS}\) and \(\left[STD\,of\,DG_{i}^{FS}-STD\,of\,\,DG_{i}^{IS}\right]\) & \(0.7066\) \\ \(AVG\,of\,\,DP_{i}^{FS}-AVG\,of\,\,DP_{i}^{IS}\) and \(\left[STD\,of\,VP_{i}^{FS}-STD\,of\,\,VP_{i}^{IS}\right]\) & \(0.5691\) \\ \(AVG\,of\,\,DP_{i}^{FS}-AVG\,of\,\,DP_{i}^{IS}\) and \(\left[STD\,of\,DP_{i}^{FS}-STD\,of\,\,DP_{i}^{IS}\right]\) & \(0.7433\) \\ \(STD\,\,of\,VG_{i}^{FS}-STD\,of\,\,VP_{i}^{IS}\) and \(\left[STD\,of\,DG_{i}^{FS}-STD\,of\,\,DG_{i}^{IS}\right]\) & \(0.6243\) \\ \(STD\,\,of\,\,VP_{i}^{FS}-STD\,of\,\,VP_{i}^{IS}\) and \(\left[STD\,of\,DP_{i}^{FS}-STD\,of\,DP_{i}^{IS}\right]\) & \(0.8125\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The correlation value of different cases. noticeably lower than the upper limit for SCSs. Furthermore, comparing the AVG of VG values between SCSs and SNSs, for obvious reasons (the lack of traffic lights) SNSs show higher \(y\)-axis values (speed average) along the \(x\)-axis (density average). Figure 4 shows _AVG of_\(D_{i}^{FS}\)vs._AVG of_\(VP_{i}^{FS}\). In the case of SCSs, the measurements for calculating \(vp\) and \(dp\) are captured only at an interval of the green time (the interval initiates 12 s after the start of the green time and finishes with the end of the green time) and when there are vehicles on the segment, therefore the vehicles are (likely) in motion and with the right to pass at the intersection; the measurements for calculating \(vg\) and \(dg\) are made (or forecasted if \(obs=0\) veh, in which case _speed_measurement_\(\cong 16.66\times 0.95\) m/s) during the green, yellow and red times; this is the reason for the higher \(y\)-axis values and lower \(x\)-axis values for SCSs in Figure 4 than in Figure 3. In the case of SNSs, the measurements for calculating \(vp\) and \(dp\) are made only when there are vehicles on the segment; for calculating \(vg\) and \(dg\) if \(obs=0\) veh (zero vehicles on the segment) we set _speed_measurement_\(\cong 16.66\) m/s, this is the reason of lower \(y\)-axis values, and higher \(x\)-axis values, for SNSs in Figure 4 than in Figure 3.  
Regarding SNSs, segment \(i=23\) has a higher priority level (used by NETEDIT to derive the right of way rules) at the intersection located at the end of segment \(i=23\) according to the travel direction; segment \(i=31\) also has a higher priority level at the respective intersection. For any other SNS, besides segments \(i=23\) and \(31\), the following is true: the intersection (at the end of the SNS) has just one input (i.e., the vehicles traveling by the SNS). In Figure 4 we notice that SCS \(i=22\) (\(y\)-axis \(\cong 12.89\) m/s) and SNS \(i=23\) (\(y\)-axis \(\cong 13.99\) m/s) seem atypical in the sense that it is expected a higher AVG of VP according to the AVG of DP. On the contrary, SCS \(i=65\) (\(y\)-axis \(\cong 14.87\) m/s) looks atypical in the sense that it is expected a lower AVG of VP.