# Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles
## 4 Evaluation
### Simulations Results  
To evaluate the cost of the collective perception service, the absolute number of CPM generated for each approach applied in the scenario was evaluated, as shown in Figure 5. The amount of CPM messages generated and received showed similar behavior to the redundancy results of detected objects. However, the VILE mechanism reduces the number of generated packets by up to 55% compared to the other approach. The most significant amount of CPM messages generated occurred when the density was 100 vehicles, with a value of 32 messages per CAV. Furthermore, we can notice a constant behavior in the number of messages generated by each vehicle and received by the RSU. This happens because the VILE mechanism chooses a single candidate to share the perception for each previously defined region. Thus, the number of vehicles does not directly influence the number of candidates chosen. The number of messages generated and transmitted by the baseline increases significantly, as there is no redundancy control mechanism. In this context, we noticed at least 25% increase in messages received by RSU.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline IVC Technology & IEEE 802.11p \\ Transmission Power & 20 mW \\ Beacon Transmission Rate & 1 Hz \\ Bit Rate & 6 Mbit/s \\ Transmission Range & 250 m \\ Maximum Interference Range & 2600 m \\ Data Message Size & 1024 Bytes \\ Scenario & Grid \\ Simulation Area & 1 km\({}^{2}\) \\ Number of Road Segments & 9 \\ Number of Vehicles & \{100, 150, 200\} \\ Number of Pedestrians & 100 \\ Vehicles Speed & Mean: 13.84 m/s (St.Dev: 5.27) \\ Sensor FoV & 360\({}^{\circ}\) \\ Range of Perception & 150m \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters.  
Unlike the communication metrics described above, which quantify the costs of the CP service, the environmental perception metrics quantify its benefit. The results discussed present the impacts of vehicular communication in CP applications. Figure 6 presents the redundancy results of objects (i.e., pedestrians and vehicles) detected for _Baseline_ and VILE. By analyzing the results of Figure 5(a), it is possible to notice a reduction in the absolute number of redundant pedestrians by 75% of VILE compared to _Baseline_. The result of the VILE mechanism is because it chooses only one node closer to the center of the region to transmit the perception with neighboring CAVs, reducing the number of objects detected more than once. Therefore, VILE can reduce the amount and processing of transmitted messages. The association between the increase in cars and the number of redundant items recognized by the system may also be observed; the number of redundant objects shared by the baseline increases by at least 25% according to the number of vehicles.  
The behavior observed in Figure 7 shows that VILE keeps the same amount of detected unique objects compared to _Baseline_. In the simulated scenario, 100 pedestrians with random positions and mobility were included. We can see that with an increase in the number of vehicles, we have an increase in the number of pedestrians detected. In the number of vehicles, the behavior is more pronounced concerning detection. The more vehicles in the scenario (200 vehicles), the greater the chances of detection and sharing of other vehicles. Thus, it is possible to conclude that the VILE mechanism meets the requirements for the operation of collective perception applications, as it maintains the same number of pedestrians and vehicles detected and shared with the other CAVs while reducing the total number of CPMs generated and transmitted.  
Figure 5: Absolute number of CPM-type messages generated and received by CAVs.  
Figure 6: Redundancy results of detected objects (pedestrians and vehicles).