## 5 Simulation Results  
For each scenario and each routing protocol, we ran 15 independent simulation experiments. The average simulation run time varied strongly depending on the simulated routing protocol. For AODV and GPSR, the average simulation run time was about 30 min on the computer equipped with Intel Core i7 Central Processing Unit (CPU) and 16 GB of Random-access Memory (RAM.) A single simulation run of the DYMO protocol took up to several hours using the same simulation workstation. As the performance metrics for the communication domain, the end-to-end delay and the message delivery probability of the messages were considered. Both indicators showed high variability across individual vehicles as they strongly depend on the distance between the EV and the vehicle. For this reason, the values of indicators were evaluated for single vehicles by averaging over delivered messages. The results of the simulation experiments are presented in Table 3. The best-case value represents the average end-to-end delay calculated over all the received messages by the vehicle, with the lowest average communication delay in simulations. The worst-case value represents the same quantity for the vehicle with the maximum average communication delay. The analogous approach was applied to the average message delivery probability. It is worth noting here that while the obtained message delivery probability values presented in Table 3 may appear to be very low even for the best-case scenarios, the values correspond to the previous observations made in the ad hoc network environment, see [44; 45] for more details. The performance of routing protocols for the two traffic scenarios differs due to the density of vehicles. Even though the traffic flow was the same in both scenarios, the lower speed limit in the Bratislava scenario implies a higher number of vehicles located in the EV's communication range. Moreover, vehicles often stopped at signalized intersections. Hence, the communication network was denser, the routing protocols could often find more than one communication route to the destination vehicle and the message delivery probability was increased. The AODV protocol, even though reaching relatively high end-to-end latency, if compared to typical expectations, is sufficient to support the dissemination of warning system messages. The achieved latency is well below the value that could substantially affect the reaction time available to drivers. Moreover, the AODV protocol achieved the highest message delivery probability among the three investigated protocols. Unlike DYMO, the AODV protocol may use Hello messages through which a vehicle periodically checks the availability of neighboring vehicles. This helps to keep the routing table more up to date at the cost of slightly increased signalization overhead. A more up to date routing table implies increased reliability and decreased latency when transmitting payload messages. The GPRS protocol achieves very low latency and the message delivery probability is lower than 24%. This comes from the routing strategies behind the GPSR protocol as also reported in [29]. If the protocolis unable to find next hop that is geographically closer to the destination, then the protocol switches to the perimeter routing mode and the algorithm traverses the network in a counter-clockwise direction. The DYMO protocol achieves the highest end-to-end delay and its message delivery probability ranges from 4% to 53% in both traffic scenarios. Please note rather high values of the standard deviation of the end-to-end delay in the case of the DYMO protocol. These are caused by extremely large end-to-end delays of the first transmitted messages. If there is no communication route to the destination vehicle in the EV's routing table, DYMO initiates the route discovery process and the first messages are transmitted only when this process is accomplished, which in our simulation experiments took several seconds. The following messages are usually delivered with a delay in the range of tens of milliseconds.