## 3 Cooperative Perception Information-Sharing
### Cooperative Perception Information-Sharing Network
#### 3.1.3 Hybrid Architecture
Therefore, market penetration is an important factor that cannot be ignored for synergistic perception effects and communication quality. When the penetration rate is too low, the communication link supporting data transmission may be unstable due to the distance, and it may even be difficult to match a suitable edge node. [PERSON] et al. [79] analyzed different combinations of vehicle V2X and sensors and pointed out that, in the case of a low penetration rate of smart vehicle market deployment in the early stages, different sensor and communication equipment deployment schemes will effectively improve the ability of cooperative perception. As shown in Figure 9, each vehicle is equipped with different configurations and quantities of communication equipment and sensors. Using cooperative perception information interaction, the impact of the low penetration rate can be effectively reduced and the range of perception can be improved. [PERSON] et al. [80] studied the accurate estimation and prediction of traffic system microstates based on the particle filter cooperative perception framework and found that the market penetration of connected autonomous vehicles has a great influence on the estimated values and predictions. When the market penetration rate is 50%, the estimated accuracy of vehicle positioning and speed is 80-90%. [PERSON] et al. [81] analyzed the demand for V2V and V2I network capacity to realize cooperative perception under different traffic densities and penetration rates. When the proportion of autonomous vehicles to the total number of vehicles is too low, it is difficult to find V2V links that support data because of the distance between autonomous vehicles. Under the conditions of limited penetration and reliability requirements, V2I communication can be used for data transmission. Then, the V2I flux from the CPM exchange was analyzed to be highest at medium permeability (0.5). Table 6, below, summarizes  
Figure 8: Application scenarios for 5G and C-V2X. the existing research on cooperative perception information-sharing and communication technology. To sum up, the cooperative perception sharing network is crucial for improving the perception capability of intelligent connected vehicles. The deployment and application \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Factors** & **Authors, Year** & **Key Research Points** & **Findings** \\ \hline \multirow{8}{*}{Vehicle Mobility} & \multirow{8}{*}{[PERSON] et al. 2021 [76]} & The network architecture of MEC and C-V2X fusion was proposed, which reduces the network transmission delay and improves the reliability of the perception system. & Distributed computing deployment can effectively reduce interaction delay. \\ \cline{2-4}  & & Explored the requirements of & The larger the bandwidth, the better the cooperative perception effect. \\ \cline{2-4}  & & Analyzed the data rate required to achieve & Derived the transmission data rate for safe driving at different driving speeds. \\ \cline{2-4}  & & Different sensor and & \\ \cline{2-4}  & & communication equipment & Different sensor combinations \\ \cline{2-4}  & & deployment schemes will & can make up for the lack of \\ \cline{2-4}  & & effectively improve the scope & low permeability. \\ \cline{2-4}  & & of cooperative perception. & \\ \cline{2-4}  & & Analyzed the impact of & When the market penetration rate is 50\%, the estimated accuracy of vehicle \\ \cline{2-4}  & & estimates and forecasts. & positioning and speed is \\ \cline{2-4}  & & Discussed the capacity requirements for vehicle & \\ \cline{2-4}  & & communication for & \\ \cline{2-4}  & & cooperative perception under & 50\% penetration. \\ \cline{2-4}  & & market penetration rates. & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Summary of the existing research on cooperative perception information-sharing communication technology according to market penetration rate and vehicle mobility. Figure 9: Illustration of the cooperative perception conception.