## 5 Simulation Results and Discussions
In the evaluation of the performance of the proposed algorithm, the other three algorithms used were as follows: A baseline algorithm, clustering with DQN based mode selection and resource allocation algorithm, and DQN based resource allocation algorithm. First, we used the SINR-based algorithm in which VEs communicate with only the V2I mode. In this algorithm, VEs associated with RRHs that served the highest SINR. It was denoted as \"Method with SINR-based V2I communication (\(BA\))\". Second, for vehicle clustering comparison, the DQN based mode selection and resource allocation algorithm in [17] was used to learn to maximize the system achievable data rate with vehicle clustering, mode selection and resource allocation method. We denote this as \"Method with clustering and DQN (\(Compare1\))\". Unlike the proposed algorithm, the communication mode and resource allocation of the vehicle were determined in consideration of the channel state of the individual vehicle in \(Compare1\). Therefore, this algorithm was used to compare performances with the proposed algorithm which is considering the sharing state of resources in use with the vehicle cluster. Third, for a comparison with the DQN based resource allocation algorithm, the algorithm in [16] was used to learn to maximize the system achievable data rate with the resource allocation method. We denote this as \"Method with DQN (\(Compare2\))\". Unlike the proposed algorithm, \(Compare2\) only considered channels and resource states that can be checked at RRHs. Therefore, this algorithm was used to compare performance with the proposed algorithm that considered local information of vehicles. The average SINR and average achievable data rate for two traffic load scenarios are compared as a function of the V2V communication distance, as displayed in Figures 4 and 5. In Figures 4 and 5, as the V2V communication distance increases, the average SINR and achievable data rate decrease because of the increasing distance between V2V VEs. The  
Figure 3: Traffic of day. proposed algorithm performs better than the other algorithms. When compared with _Compare1_, the clustering algorithm _Compare1_ has a higher ratio of V2I mode VEs and higher interference, resulting in lower average SINR. The achievable data rate also decreases due to increasing interference. This is because the proposed algorithm selects the VE with the highest SINR as CH and enters the cluster with the highest SINR. Compare1 exhibits lower SINR and achievable data rate than _Compare2_, which does not employ a clustering method. _Compare2_ selects a communication mode in which VEs can receive the best SINR. Because the proposed algorithm allocates resources in units of vehicle clusters, the average SINR and achievable data rate are higher than those of _Compare2_ due to low interference. Compared to the low traffic scenarios, the performance of high traffic scenarios is observed to be better. This is because the vehicle density in high traffic scenarios is higher than the density in low traffic scenarios making V2V communication possible with VEs relatively closer to each other. Figure 4: Comparison of average SINRs with various V2V distance: (**a**) With low scenario; (**b**) with high scenario. The outage probability for the different traffic scenarios are compared as a function of the V2V communication distance, as shown in Figure 6. The comparisons included only three algorithms: The proposed algorithm, _Compare1_, and _Compare2_. _BA_ was excluded because of its low outage probability as it only communicates with V2I through SINR-based user association. In the case of the proposed algorithm and _Compare1_, both methods employed clustering because the V2V communication ratio was high. The outage probability of the proposed method was lower than that of _Compare2_ however, due to low interference. When the V2V communication distance is increased, CH is capable of receiving optimal SINR, thus minimizing the interference.