## 5 Simulation Results
### Results of the \(2^{k}\) Factorial Analysis  
In this section, we use the \(2^{k}\) factorial analysis [6] to determine the most relevant factors that govern Warning Message Dissemination performance. We consider 9 factors, previously presented in Section 4. They are listed in Table 5. We tag each of the factors with A, B, C,..., I accordingly, as stated in the table. Thereafter, we specify two representative and basically opposite scenarios, which are described by two different levels, _i.e._, Level \(-1\) and Level 1. Each level provides different parameter values to define the scenario.  
After having executed the \(2^{k}\) factorial analysis, Table 6 indicates the percentage of variation of each studied metric explained by each factor. The more the percentage of variation, the more impact this factor has in the measured metric.  
The results of our \(2^{k}\) factorial analysis show that:  
* The average time required to complete the propagation process is largely affected by the RPM used (H), the simulated roadmap (I), the combination of the density and the mobility model (BG), and the combination of the density and the RPM used (BH).
* The average number of blind vehicles is largely affected by the density of vehicles (B), the RPM used (H), the simulated roadmap (I), and the combination of the density and the RPM used (BH).  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Factor** & **Level –1** & **Level 1** \\ \hline warning vehicles (A) & \(3\) & \(10\) \\ density of vehicles (B) & 25 vehicles/km\({}^{2}\) & 100 vehicles/km\({}^{2}\) \\ channel bandwidth (C) & 3 Mbps & 6 Mbps \\ broadcast scheme (D) & location-based [27] & eMDR [21] \\ normal messages priority (E) & AC0 & AC3 \\ periodicity of messages (F) & 1 packet/s & 20 packets/s \\ mobility model (G) & Krauss modified [37] & Wagner [38] \\ radio propagation model (H) & Two Ray Ground & RAV [4] \\ roadmap (I) & New York & Rome \\ \hline \hline \end{tabular}
\end{table}
Table 5: Factors considered and their values.  
* The average number of packets received per vehicle is largely affected by the density of vehicles (B), the RPM used (H), and the simulated roadmap (I).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**Variation Explained (\%)**} \\ \cline{2-3}
**Factors** & _Warning Notification Time_ & _\% of Blind Vehicles_ & _Number of Packets Received_ \\ \hline \(A\) & 5.67 & 1.88 & 1.13 \\ \(B\) & 0.89 & **8.61** & **28.55** \\ \(C\) & 0.02 & 0.00 & 3.63 \\ \(D\) & 3.22 & 0.14 & 3.28 \\ \(E\) & 0.00 & 0.00 & 0.00 \\ \(F\) & 0.00 & 0.00 & 0.00 \\ \(G\) & 0.47 & 2.70 & 0.23 \\ \(H\) & **20.72** & **49.87** & **36.26** \\ \(I\) & **9.35** & **14.07** & **7.92** \\ \(AB\) & 0.37 & 1.30 & 0.05 \\ \(AC\) & 0.06 & 0.00 & 0.19 \\ \(AD\) & 0.77 & 0.03 & 0.59 \\ \(AE\) & 0.00 & 0.00 & 0.00 \\ \(AF\) & 0.00 & 0.00 & 0.00 \\ \(AG\) & 0.01 & 0.35 & 0.61 \\ \(AH\) & 0.09 & 1.87 & 0.29 \\ \(AI\) & 0.90 & 0.15 & 0.01 \\ \(BC\) & 0.05 & 0.00 & 2.39 \\ \(BD\) & 1.03 & 0.06 & 0.22 \\ \(BE\) & 0.00 & 0.00 & 0.00 \\ \(BF\) & 0.00 & 0.00 & 0.00 \\ \(BG\) & **33.35** & 0.42 & 0.56 \\ \(BH\) & **14.40** & **9.09** & 5.62 \\ \(BI\) & 1.06 & 5.37 & 4.21 \\ \(CD\) & 0.07 & 0.00 & 0.06 \\ \(CE\) & 0.00 & 0.00 & 0.00 \\ \(CF\) & 0.00 & 0.00 & 0.00 \\ \(CG\) & 0.00 & 0.00 & 0.05 \\ \(CH\) & 0.01 & 0.00 & 1.59 \\ \(CI\) & 0.03 & 0.00 & 0.51 \\ \(DE\) & 0.00 & 0.00 & 0.00 \\ \(DF\) & 0.00 & 0.00 & 0.00 \\ \(DG\) & 5.26 & 0.06 & 0.25 \\ \hline \hline \end{tabular}
\end{table}
Table 6: The percentage of variation explained using the sign table method up to the combination of 2 factors. Highlighted values indicate representative variations.  
Based on the above outcome, we can state that the key factors to be accounted for when studying warning dissemination systems are the density of vehicles, the radio propagation model, and the simulated roadmap. We now perform a detailed study to evaluate the impact of the most representative factors one by one.