## 5 Measurements Results  
To validate previous simulation results, several measurement points were collected in the real scenario presented in the Section 3.3, with the previous explained deployed equipment. Figure 16 exhibits the results gathered throughout the measurements campaign, in markers from \(P_{1}\) to \(P_{31}\) as represented by the layout in Figure 8. The empirical data is represented in circles joined by linear interpolation, where every point is spaced by 1.2 meters, starting from 1.2 to 37.2 m in the x-axis. The 3D-RL results of the simulation carried out on the virtual stage, under the conditions of the measurement campaign, are illustrated in the same figure by red \"+\" symbols. The root-mean-square error (RMSE) between measurements and simulation is 2.91 dB, showing good agreement between simulations and the empirical data. To compare with related work in the literature, a study carried out by [PERSON] et al. (2018) based on the characterization of the wireless channel in a V2I scenario, has been considered. The work analyzes different scenarios, where the fitted values for a CI free-space model are obtained in terms of its PLE and shadow fading (\(\sigma_{SF}\)). Using the PLE \(n=1.98\) and a \(\sigma_{SF}=3.62\) dB, which is the best fit determined in their investigation for the LOS cases, the received signal power estimation is plotted in Figure 16 following the CI free-space model. The RMSE of this estimate is 5.02 dB, an error greater than that of the 3D-RL simulation presented in this work. This shows the close relationship of the PLE and the \(\sigma_{SF}\) with the specific environment that it intends to estimate. The scenario in which  
Figure 16: Measurement results for \(P_{1}\) to \(P_{31}\) locations (see Figure 8 for reference), 3D-RL simulation results for these spatial positions, and a CI free-space model approximation (\(n=1.98\)\(\sigma_{SF}=3.62\) ). \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Omnidirectional Pattern**} & \multicolumn{2}{c}{**Directional Pattern**} \\ \hline  & **Car** & **Bus** & **Car** & **Bus** \\  & **Obstruction** & **Obstruction** & **Obstruction** & **Obstruction** \\ \hline \(\overline{PLE}\) & - & - & 2.11 & 2.84 \\ \(\overline{\sigma_{SF}}\) (Path Loss) & - & - & 11.09 dB & 15.69 dB \\ Mean Excess Delay & 245.7 ns & 227.8 ns & 294.6 ns & 221.5 ns \\ RMS DS difference & 3.24 ns & 21.14 ns & 2.16 ns & 3.74 ns \\ \(\sigma_{R1}^{2}\) (RMS DS) & 2.35 ns & 14.25 ns & 6.23 ns & 26.44 ns \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation Results. the measurements and the 3D-RL simulation occur presents a favorable environment to the wave propagation, with abundant scatterers on both sides of the LOS path. Large metal elements are also on the sides, influencing better signal reception throughout the path. As a result, the use of PLE based on generic scenarios can lead to estimation errors, while deterministic simulations such as RL can better demonstrate the phenomena that characterize a given scenario. The second set of measurements were taken at the opposite sidewalk, marks from \(Pc_{1}\) to \(Pc_{15}\) measurements points in Figure 8. Figure17 shows the collected data, where each point is spaced by 2 m, starting from \(x=0\) (\(Pc_{1}\)) to \(x=28\) (\(Pc_{15}\)). Please note that Figure 8 is for representation and it is not render at the exact scale. These measurements emulate a V2I (RSU) communication when the latter is on the other side of the avenue. The corresponding 3D-RL software simulation results are plotted together with the empirical values, where the 3D-RL data points are denoted by red \"+\" symbols. The RMSE between simulation and the experimental measurements is 4.06 dB, being higher in this case because the measurements were made with different vehicle distributions at every point (\(Pc_{1}\) to \(Pc_{15}\)).