# Intelligent Traffic Model for Unmanned Ground Vehicles Based on DSDV-AODV Protocol
## 2 Method
### Dsdv-Aodv
#### 2.3.1 Work Mechanism of the Protocol
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{2}{c}{**(a) 500 Fixed Nodes**} & \multicolumn{2}{c}{**(b) 500 Fixed Nodes + 500 Mobile Nodes**} \\ \hline
** AODV** & **DSDV** & **DSDV-AODV** & **AODV** & **DSDV** & **DSDV-AODV** \\ \hline  & \multicolumn{4}{c}{QoS parameter (kbps)} \\ \hline
5.16 & 6.20 & 1.456 & 6.97 & 9.2 & 23.2 \\
70.8 & 78.1 & 84.2 & 363.97 & 352.4 & 385.6 \\
63.5 & 62.6 & **69.8** & 328.5 & 331.9 & **342.5** \\ \hline  & \multicolumn{4}{c}{Delay parameter (second)} \\ \hline
0.00216 & 0.00218 & 0.000267 & 0.00495 & 0.00425 & 0.00028 \\
0.00171 & 0.00169 & 0.00166 & 0.00169 & 0.00164 & 0.00143 \\
0.00148 & 0.00147 & **0.00142** & 0.00192 & 0.00195 & **0.00133** \\ \hline  & \multicolumn{4}{c}{Throughput parameter (kbps)} \\ \hline
5.1 & 5.31 & 5.8 & 25.1 & 8.3 & 40.54 \\
73.9 & 80.7 & 88.2 & 406.2 & 410.1 & 412.2 \\
67.2 & 68.3 & **74.1** & 367.2 & 365.39 & **372.3** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Scenario 03 results. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & \multicolumn{2}{c}{**(AODV, DSDV)**} & \multicolumn{2}{c}{**DSDV-AODV**} \\ \hline  & 20 fixed nodes & 20 fixed nodes + 20 mobile nodes & 20 fixed nodes & 20 fixed nodes +20 mobile nodes \\ \hline QoS (kbps) & (386.2, 455.3) & (484.3, 456.3) & 637.5 & 640 \\ \hline Delay (second) & (0.0043, 0.0046) & (0.0025, 0.0026) & 0.0018 & 0.0012 \\ \hline Throughput (kbps) & (402.63, 432.3) & (578.7, 582.63) & 629.437 & 627.49 \\ \hline  & 50 fixed nodes & 50 fixed nodes +50 mobile nodes & 50 fixed nodes +50 mobile nodes \\ \hline QoS (kbps) & (107.8, 112.6) & (144.29, 153.9) & 126.1 & 192.47 \\ \hline Delay (second) & (0.00183, 0.00178) & (0.00167, 0.00157) & 0.00168 & 0.00062 \\ \hline Throughput(kbps) & (156.5, 168.3) & (111.39, 117.39) & 260.53 & 130.8 \\ \hline  & \multicolumn{4}{c}{500 fixed nodes} & 500 fixed nodes +500 mobile nodes & 500 fixed nodes +500 mobile nodes \\ \hline QoS (kbps) & (63.5, 64.6) & (328.5, 331.9) & 69.8 & 342.5 \\ \hline Delay (second) & (0.00148, 0.00147) & (0.00192, 0.00195) & 0.00142 & 0.00133 \\ \hline Throughput (kbps) & (67.2, 68.3) & (367.2, 365.39) & 74.1 & 372.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Results of all parameters averaged for each scenario. ## 4 Conclusions

Based on the implementation, testing, and analysis of data communication simulation and analysis on intelligent traffic lights using AODV and DSDV-AODV protocols applied on 802.11p networks, it can be concluded that the DSDV-AODV routing protocol is superior to AODV based on the results of performance parameters for all three scenarios in the research analysis. In contrast, DSDV-AODV has the smallest average delay (0.00062 s), while AODV and DSDV have the smallest average delays (0.00167 and 0.00157 s) among the values of the second scenario with 50 fixed nodes and 50 mobile nodes. Additionally, the results for the throughput parameter in DSDV-AODV exceed the two other scenarios, with a value of 629.43 bits/s in the first scenario. The lowest AODV routing in the third scenario yields a value for the network QoS parameter of 63.5 bits/s, but the DSDV-AODV routing yields a value of 69.8 bits/s. In comparison to the other two cases, the scenario with 50 fixed nodes and 50 mobile nodes produces the best results for the metric parameters. Although the outcomes for network QoS parameters are unsatisfactory, the inclusion of mobile nodes to the topology improves the node parameter delay and throughput. In the end, it can be said that the contributions of this research suggest a novel model to enhance intelligent traffic lights using the DSDV-AODV protocol for adaptively picking the appropriate routing path for Unmanned Ground Vehicles by using extensive simulations. We verified our analytical QoS, delay, and throughput models, and proved the new enhanced performance of intelligent traffic lights.