# Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles
## 3 Collective Perception Mechanism for Autonomous Vehicles
### Vile Operation  
In summary, the VILE mechanism considers tree phases for CP service, namely, knowledge, selection, and perception phases. The VILE mechanism takes into account the existence of a set \(H\) of hexagonal regions that divide a given map, as shown in Figure 2, which depicts the division of the areas considered for the mechanism's selection phase. Mapping is a critical component of autonomous sensing and navigation systems since it provides the CAV with the ability to locate and plan a collision-free course, as well as a means of communication between people and the CAV. The hexagonal grid-based map is one of the most used approaches for representing the surroundings. The RSUs have global knowledge of the regions present in their coverage radius, but the distribution is global and not associated with a specific RSU. VILE considers that an area segmentation algorithm, such as the one presented by Uber [47], was used to partition the scenario into hexagons. The VILE mechanism considers that each hexagonal region \(h\) of the set of regions \(H\) has a fixed size \(S\) and diameter equal to the maximum range of a vehicle's sensors. Grid map systems are essential for analyzing enormous geographical perceptions systems since they segment Earth into recognizable grid cells [48; 49]. A hexagonal grid map can be used for mapping static and dynamic environments. The shape of the cell is not essential for dynamic approaches, but the advantages of the shape are preserved. Other publications have already shown the advantages of dividing areas using hexagons [50; 51]. Fewer hexagonal sections are needed to represent the map, which reduces the computing time and storage requirements. Another advantage of employing hexagonal areas is that sampling using hexagons results in minimal quantization error for a given sensor's resolution capacity [49]. First, the distance between a particular cell and its immediate neighbors is the same in all six principal directions; curved structures are represented more precisely than rectangular regions [50; 51]. In that context, in the knowledge phase, the RSU collects information shared by the CAVs based on position, speed, and orientation. Following, the selection phase chooses the CAV \(v_{i}\) closest to the center position of the hexagonal region \(h_{i}\) to share the set \(O_{vi,t}\) of detected objects with the other vehicles after the end of the time window \(W\), as shown in Figure 3. This CAV is in charge of representing the perception in the defined region. Algorithm 1 provides a brief explanation of how the VILE mechanism was implemented and how the selection process is carried out based on the distance between the position of each CAV and the center of each hexagonal region. The parameters used to begin this processes are the hexagonal region's center position \(L\) and the CAVs set \(V\) under the RSU cover selected to share their sensor perception with other vehicles. Figure 2: VILE knowledge phase. In this way, Algorithm 1 describes the process of the VILE. The set of vehicles \(V\) and the hexagonal regions \(H\) created by RSU that divide a given map are provided to VILE. In each vehicle inside the RSU coverage area, the algorithm identifies the defined hexagonal region \(h\) according to each \(v_{i}\) position (Lines 7-9). In the case of the \(v_{i}\) position information present in the \(h\) region of the RSU, the RSU can calculate the distance between the position of the \(v_{i}\) and the center position of the hexagonal region \(h\). For this, VILE applied Euclidean distance to calculate the smallest distance between two specific points (Line 10). If the calculated distance \(d(L_{v_{i}},L_{h})\) is the shortest distance, compared with \(minDistance_{h}\), among the set of CAVs in the region \(h\), then the CAV is added to the set of selected vehicles \(V_{H}\) (Lines 11-12). Finally, the RSU sends the message on the network and requests the selected CAVs about the perception of the region (Line 13).