Some researchers aim to improve vehicular communication systems by proposing an integrated framework that allows networking, caching, and computing [31]. Some researchers provide a clear overview of the evolution of the long-term evolution vehicle (LTE-V) and its modes 3 and 4, as well as the practice of 5G V2V technology [32], the standardization of radio access technologies such as 802.11 bd and NR V2X (supplementary of vehicular sensors) and their prospects [33; 78], the standardization of LTE V2X in the third generation partnership project (3 GPP) [18; 77], etc. Except for the most cited article by [PERSON] et al., which envisions the next-generation technology, throughout most references in this cluster, the researchers notice the main idea is how different wireless access technologies enable V2X and their features rather than merely about AI. As the cluster emerges, the research base is expected to be extended in the foreseeable future. **Research Frontier**  
Nowadays, IoV is in a paramount position in either economic development or international prestige, and V2X communication is a highly expected subject. The United States pays a lot of attention to the development of DSRC, which enables V2V and relative communications [20]. Studies have been conducted to analyze the strengths and limitations of DSRC and cellular network communication technologies, as well as to envision the impact of 5G technology [20]. Beyond this, researchers are eager to fully understand the concept, history, features, and application of VANET, the 5G V2X, and the possible 6G V2X [29; 35; 79; 80]. Researchers also wish to know how machine learning technology helps the development of VANET [35] in either security systems [34] or detection accuracy and efficiency [36]. Moreover, machine learning in 6G V2X and mobile edge computing are reviewed [79; 81]. In some review articles, researchers focus on the cellular vehicle-to-everything (C-V2X) in 3 GPP, especially the sidelink air interface [82]. The aforementioned studies were conducted around 2021; thus, researchers who are interested in the integration of AI technology and vehicular networking could go through these articles to gain the newest research status. Cluster 3: intrusion detection system; using fog computing; routing protocol  
## Research Base  
References with high citation rates were published mainly in 2016 and 2017, and the major research direction is the security challenges of VANETs. In this period, VANETs were one of the popular topics that drew scholars' attention. Researchers would like to figure out the types of attacks and the corresponding detection mechanisms [37; 38], the suitable types of protocols and applications [39], and the feasible authentication scheme [40]. Except for reviewing literature in the field of study, researchers also look for different approaches to improve vehicular trust management. For example, researchers propose an attack-resistant trust management scheme (ART) for VANETs to detect and deal with attacks and evaluate the trustworthiness of data [41]. Researchers also concern themselves with the effects of security attacks on vehicular communication channels and sensor tampering on ICVs and their countermeasures [83]. Besides, some researchers discuss the application of UAVs in the establishment of ITS [84]. References in this cluster seem to be solutions to vehicular security issues other than blockchain.