## 3 Results
### Co-Citation and Cluster Analysis  
#### 3.3.1 Citing Articles and Cited References  
CiteSpace identifies the major clusters of research in the field by analyzing the literature citation data. The analysis obtained more than 30 clusters, including 15 main clusters and 779 inter-cluster nodes. The modularity of the clusters, represented by Q = 0.6825, indicates an outstanding inter-cluster network structure as Q > 0.3. The silhouette of all clusters, with a value of S = 0.8541, falls within the range of 0.5 < S < 1, indicating a reasonable intra-cluster similarity. These values demonstrate excellent clustering that is capable of analysis. For each cluster, major words from the titles of the cited literature are extracted as labels. For example, in Table 1, the most cited literature in Cluster 0 contains VEHICULAR CLOUD COMPUTING, USING VANET, etc. All 15 clusters have good structure and high similarity values. Cluster 0 (VEHICULAR CLOUD COMPUTING) is the largest; Cluster 1 (TRUST MANAGEMENT), Cluster 2 (LEARNING-BASED RESOURCE ALLOCATION), and Cluster 3 (INTRUSION DETECTION SYSTEM) are relatively large clusters in the co-citation analysis and are the main clusters in the field of study (Table 1 and Figure 9). The timelines of co-citation clusters (Figure 10) depict each cluster as a line, with the size of the cluster during the corresponding period indicated by the size of the dots. Cluster 0 (VEHICULAR CLOUD COMPUTING) emerges earliest, around 2014-2015, as a large cluster, indicating the early research on ICV road safety focused on vehicular cloud computing and related themes. Cluster 1 (TRUST MANAGEMENT), Cluster 2 (LEARNING-BASED RESOURCE ALLOCATION), Cluster 6 (V2I COMMUNICATION), Cluster 7 (CONTROL AREA NETWORK), Cluster 8 (CONVOLUTIONAL NEURAL NETWORK), and Cluster 13 (RECONFIGABLE INTELLIGENT SURFACE) emerged in  
Figure 7: Keyword density visualization. Red represents high density and blue represents low density. later periods. Since 2019, the main research in this field has revolved around automotive information communication and intelligent control technology. Cluster 2 (LEARNING-BASED RESOURCE ALLOCATION), Cluster 6 (V2I COMMUNICATION), and Cluster 7 (CONTROL AREA NETWORK) are the representatives. In addition, the information security of smart vehicle users is attracting increasing attention as the techniques improve. Cluster 1 (TRUST MANAGEMENT) and Cluster 5 (KEY AGREEMENT PROTOCOL) are the representatives (Figure 10). The top five clusters will be discussed in this study. For each of them, major cited and citing literature will be analyzed to determine the research base and research frontier, and the top five cited and citing literature will be listed in this section. **Cluster#0 VEHICULAR CLOUD COMPUTING**  
Cluster 0 contains wording like VEHICULAR CLOUD COMPUTING, USING VANET, DATA MANAGEMENT PERSPECTIVE and so on. The most frequently cited work in cluster 0 is by [PERSON], et al. (2014) [9], which overwhelmingly dominates the field of research. Other cited literature has a frequency of no more than half. [PERSON]. (2014) [10] is cited 40 times and ranked second. [PERSON]. (2014) [11] and [PERSON]. (2012) [12] are the third, and each has been cited more than 30 times. [PERSON]. (2014) [13] is ranked fifth. The top five citing authors are [PERSON] (2015) [14], [PERSON] (2015) [15], [PERSON] (2018) [16], [PERSON] (2015) [17], and