## 3 Vehicle Clustering Algorithms
### Vehicle Clustering Method Based on DBSCAN Algorithm
Analysis of RSU Deployment Considering Communication Radius

Based on the simulation environment described in Section 4.1, with a mixed traffic density of 0.03, we conducted 4000 simulations to examine the impact of CAV permeability on network connectivity. It can be observed from Figure 8 that, when the communication radius of RSU remains constant, the network connectivity increases with an increase in CAV permeability. Moreover, for a given CAV permeability, a larger communication radius of RSU leads to higher overall network connectivity. When the communication radius of RSU is less than 100 m, the network connectivity is almost non-existent. On the other hand, when the communication radius exceeds 400 m, the network connectivity remains above 50%, even at lower CAV permeability. According to the analysis in Section 2.2, the vehicle cluster length is the distance between the cluster head and the farthest CAV vehicle in the mixed vehicle cluster plus twice the CAV communication radius, i.e., \(\mathrm{L_{R}=E(c)+2R_{V}}\). The relationship between the vehicle communication radius and the average vehicle cluster length is obtained through MATLAB simulation analysis, as shown in Figure 9. From Figure 9, it can be observed that the average vehicle cluster length varies with the CAV permeability in the mixed traffic flow. When the vehicle communication radius is the same, a higher CAV permeability leads to a longer average vehicle cluster length. Similarly, when the CAV permeability is the

Figure 8: Relationship between permeability and network connectivity at different communication radii. Figure 7: Comparison of network performance with different permeabilities. same, a larger vehicle communication radius results in a greater average vehicle cluster length. These findings align with real-world observations. Based on the RSU deployment scheme described in Section 2.1, the RSU deployment interval is the sum of the average vehicle cluster length and twice the RSU communication radius, i.e., \(\rm{D_{RSU}}=L_{R}+2R\). The vehicle communication radius was set to a mean value of 300 m, and the relationship between the CAV permeability and the RSU deployment interval was obtained through simulation analysis, which is shown in Figure 10. From this, it can be observed that when the CAV permeability in the mixed traffic flow is relatively low, e.g., 0.3, the RSU communication range can be adjusted to 500 m, and the RSU deployment interval is 1624 m. According to Figure 6, the network connectivity is above 95% under this configuration. On the other hand, when the CAV permeability is relatively high, e.g., 0.7, the RSU communication range can be reduced to 300 m, and the RSU deployment interval is 1317 m. As indicated in Figure 8, the network connectivity is close to 100% under this configuration. #### 4.3.2 The Deployment Analysis of Roadside Units (RSUs) Considering Mixed Traffic Flow Density

Figure 11 illustrates the impact of different values of highway mixed traffic flow density and permeability on network connectivity when the RSU vehicle radius is equal to

Figure 3:0 Relationship between permeability and RSU deployment intervals at different communication radii. Figure 3:1 Relationship between permeability and vehicle cluster length under different vehicle communication radii. the vehicle communication radius and takes an average value of 300 m. From Figure 11, it can be observed that when the mixed traffic flow density is below 0.03, the network connectivity is too low. Therefore, the minimum density threshold for the mixed traffic flow is set to 0.03. On the other hand, when the traffic flow density is greater than 0.05 and the CAV permeability is higher than 0.2, the network connectivity is consistently above 80%.