# V2X-Based Highly Reliable Warning System for Emergency Vehicles
## 5 Analysis and Discussions
J2H has a lower rate of increasing delay until the number of vehicles is 150, after which the delay increases at a slightly higher speed and reaches a maximum delay of 0.013 s. On the other hand, the OTREM has a delay of 0.015 s, and CRA has 0.025 s.  
Figure 5: Analysis of transmission delay in transmitting alert messages with low density of vehicles. In order to estimate the constant rate of transmission delay, we simulated the approaches five times, each with a low density and high density of vehicles, and the results are plotted in Figures 7 and 8. On the analysis of maximum transmission delay, it is observed that both the J2H and OTREM approaches have a similar rate of increase in the transmission delay, whereas the CRA possesses an extremely high transmission delay versus the J2H and OTREM approaches. From Figure 7, it is observed that the J2H possesses a maximum transmission delay of 0.01 s, and OTREM has 0.03 s. However, the CRA approach has a maximum of 0.35 s. Similarly, from Figure 8, when the density of vehicles reaches a maximum of 500 vehicles, the approaches J2H and OTREM have maximum transmission delays of 0.05 and 0.07 s, respectively. However, the CRA approach reaches 0.35 s when the number of vehicles is 80. The reason behind the efficiency of J2H is that the traffic density at traffic signals following normal signal sequence is considerably higher when compared to traffic density at traffic signals using our J2H approach of signal customization at the time of EV approach. This is because knowing the EV movement in prior J2H will customize the traffic signal in such a way to minimize the traffic density in the EV route. Figure 6: Analysis of transmission delay in transmitting alert messages with high density of vehicles. Figure 7: Analysis of maximum transmission delay in transmitting alert messages with low density of vehicles. The number of alert packets transmitted in the J2H approach when time changes is plotted in Figure 9 for the conditions with high traffic density and low traffic density. When the network has a high density of vehicles, the J2H approach transmits a maximum of 65 data packets, whereas with low density of vehicles, the J2H approach transmits a maximum of 80 data packets. This is because the usage of V2V for alert passing and J2H for customizing the traffic signals helps in reducing traffic congestion, thereby decreasing traffic density. Thus, from the above graphs, we can analyze the traffic density at each signal, and the alert packets are then transmitted accordingly. The comparative analysis of throughput for the approaches J2H, OTREM, and CRA is plotted in Figure 10. From Figure 10, it is observed that the J2H approach has higher throughput than the OTREM and CRA. When it is 75 s, the throughput of J2H, OTREM, and CRA reaches 4600, 410, and 2250 Kbps, respectively. As, J2H uses ITS, which does not require any intermediate RSU, the response time for customizing the traffic signals will be low. RSU has a high processing time, resulting in a high response time from the traffic signals. Figure 8: Analysis of maximum transmission delay in transmitting alert messages with high density of vehicles. Figure 9: Analysis of the number of alert packets transmitted in J2H approach when time changes with low density and high density of vehicles. Thus, from the overall analysis, we can observe that the proposed J2H approach has higher efficiency in the dissemination of warning data packets and optimizes the path of EV to travel. In this way, the EVs can overcome the time delay to reach the destination by choosing the fastest route based on traffic density. Traffic congestion is overcome by customizing the traffic signals, and the path blockage can be cleared by V2V communication.