## 6 Discussion
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**All Cars**} & \multicolumn{3}{c}{**Platoon Members**} \\ \cline{3-6}  & \begin{tabular}{c} **Travel** \\ **Time** \\ \end{tabular} & \begin{tabular}{c} **Fuel** \\ **Consum.** \\ \end{tabular} & \begin{tabular}{c} **Travel** \\ **Time** \\ \end{tabular} & \
\begin{tabular}{c} **Fuel** \\ **Consum.** \\ \end{tabular} &
\begin{tabular}{c} **Avg. Platoon** \\ **Length** \\ \end{tabular} \\ \hline Configuration 1 (One-hop VTLs) & 0.943 & 0.872 & N/A & N/A & N/A \\ \hline Configuration 2 & VNIBR-R & 0.999 & 0.998 & 0.987 & 0.991 & 2.19 \\ (Traditional traffic lights + platoons) & VNIBR-E & 0.998 & 0.997 & 0.981 & 0.991 & 2.26 \\  & VNIBR-E & 0.998 & 0.997 & 0.989 & 0.992 & 2.13 \\  & VVAADDV & 0.999 & 0.999 & 0.994 & 0.995 & 2.07 \\ \hline  & VNIBR-R & 0.931 & 0.851 & 0.272 & 0.329 & 3.54 \\ Configuration 3 & VNIBR-P & 0.950 & 0.878 & 0.138 & 0.198 & 3.77 \\ (VTLs + platoons) & VNIBR-E & 0.937 & 0.877 & 0.224 & 0.251 & 3.61 \\  & VVAADDV & 0.944 & 0.880 & 0.319 & 0.362 & 3.15 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results for high traffic density (time and fuel normalized regarding best average values from configuration 0). Our proposal for VTL management also has noticeable impact in the average length of the platoons, because it promotes the join maneuvers. Without VTLs, in configuration 2, the average length of the platoons is close to the minimum (2) and it is common that an existing platoon is split at an intersection, since not all the members manage to cross according to the traditional traffic lights or the stop/yield signals. Finally, it can be seen that the underlying communication protocols have noticeable impact in the performance of configuration 3 and, to a lesser extent, configuration 2 too. VNAODV yields the worst performance systematically, because it stores and processes routing information in every virtual node (not only at the intersections), which implies slower action and more possible points of failure. These shortcomings are more noticeable with light traffic, when there are fewer cars in general to support every virtual node. Among the three variants of VNIBR, the proactive one achieves the best results with medium and high vehicular densities, because greater stability of the virtual nodes and lower mobility of the vehicles lead to a more usable tree of routes between intersections, which speeds up the dissemination of platoon announcements and helps to increase the accuracy of the arrival estimations. In cases of low vehicular density, the reactive and encounter-based versions get better results, since VNIBR-P has more trouble to deal with the high mobility and the frequent QoS changes. In any case, it is worth noting that, whereas other communication services supported by the infrastructure of virtual nodes could be severely affected by frequently empty VN regions (see [12; 13]), the management of VTLs and platoons is quite resilient, because the information exchanged among the vehicles is only relevant in their vicinity, and empty VN regions (particularly, empty intersections) mean faster transit for both individual cars and platoons.