## 5 Simulation Results
In summary, only the AODV routing protocol reached sufficiently high reliability and it will be further employed by the PEEV-WS. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Parameter**} & \multirow{2}{*}{**Scenario**} & \multirow{2}{*}{**Vehicle**} & \multicolumn{4}{c}{**Protocol**} \\ \cline{3-6}  & & & **AODV** & **GPSR** & **DYMO** \\ \hline \multirow{8}{*}{**Average end-to-end delay of EV to vehicle communication (ms)**} & \multirow{8}{*}{Best} & **Value** & **0.60** & **0.73** & **48.03** \\ \cline{3-6}  & & & \(\sigma\) & 0.64 & 1.17 & 48.03 \\ \cline{3-6}  & & & CI95 & 0.02 & 0.10 & 4.77 \\ \cline{3-6}  & & & **Value** & **37.87** & **13.65** & **2668.90** \\ \cline{3-6}  & & & \(\sigma\) & 230.88 & 84.71 & 4588.95 \\ \cline{3-6}  & & & CI95 & 14.62 & 13.88 & 431.73 \\ \cline{3-6}  & & & **Value** & **0.53** & **0.59** & **34.90** \\ \cline{3-6}  & & & \(\sigma\) & 0.12 & 0.11 & 132.18 \\ \cline{3-6}  & & & CI95 & 0.01 & 0.01 & 8.10 \\ \cline{3-6}  & & & **Value** & **34.95** & **6.31** & **984.85** \\ \cline{3-6}  & & & \(\sigma\) & 252.82 & 13.14 & 2713.85 \\ \cline{3-6}  & & & CI95 & 12.37 & 1.56 & 174.98 \\ \hline \multirow{8}{*}{**Average message delivery probability (\%)**} & \multirow{8}{*}{Best} & **Value** & **99.89** & **23.77** & **43.72** \\ \cline{3-6}  & & & \(\sigma\) & 0.20 & 2.71 & 3.86 \\ \cline{3-6}  & & & CI95 & 0.10 & 1.37 & 1.95 \\ \cline{3-6}  & & & **Value** & **22.89** & **1.11** & **3.67** \\ \cline{3-6}  & & & \(\sigma\) & 4.58 & 0.35 & 1.59 \\ \cline{3-6}  & & & CI95 & 2.32 & 0.18 & 0.81 \\ \cline{3-6}  & & & **Value** & **99.90** & **23.39** & **53.41** \\ \cline{3-6}  & & & \(\sigma\) & 0.20 & 2.62 & 4.61 \\ \cline{3-6}  & & & CI95 & 0.10 & 1.33 & 2.33 \\ \cline{3-6}  & & & **Value** & **41.54** & **3.31** & **11.15** \\ \cline{3-6}  & & & \(\sigma\) & 16.24 & 0.63 & 8.03 \\ \cline{3-6}  & & & CI95 & 8.22 & 0.32 & 4.07 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of routing protocols. We report the average values for the end-to-end delay of the EV to vehicle communication and the message delivery probability calculated over 15 independent simulation runs and over messages delivered to the best-case and the worst-case vehicles (row Value). The corresponding standard deviation (row \(\sigma\)) and the size of the 95% confidence interval (row CI95) are reported as well. When forming the emergency lane, the number of vehicles that need to be informed about an approaching EV depends on the traffic conditions (speed and traffic density). For example, considering the required communication range of 1000 m and the uniform separation between vehicles of 25 m, the number of vehicles that could occupy the emergency lane is 40. Through simulations, we investigated the number of vehicles the EV can communicate to. When using the default configuration of the AODV protocol, we found out that in the Bratislava scenario, the EV was able to communicate with all relevant vehicles, however, in the Zilina scenario, the EV could simultaneously communicate at maximum to 12 destination vehicles only, which was not enough to communicate with all relevant vehicles. Close investigations revealed that this limitation is caused by the parameter settings affecting the routing mechanism, in particular, it is given by the maximum number of route request messages that can be generated in one second, \(\rho_{max}\). This value limits the number of messages that are sent out within one cycle by the EV, to discover the existing communication routes in the network. In the AODV protocol specification, this value is given by the value of the parameter RREQ_RATELIMIT. A relationship between the number of successfully addressed vehicles and the value of \(\rho_{max}\) is analyzed in Figure 6a while simulating the Zilina scenario. By increasing the value \(\rho_{max}\), the number of vehicles that the EV can communicate to increases as well.