The application of vehicular Ad Hoc networks (VANET) is crucial for intelligent transport systems (ITS). This VANET application also facilitates vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Here, maintaining Quality of Service (QoS) and ensuring efficient routing are still difficult tasks because of the following factors: high mobility, frequent topology changes, and variable node densities. For enhanced network stability and resource optimization, cluster- based (CB) routing protocols (RP) with the application of intelligent cluster head (CH) selection mechanisms have become an effective method. For VANET, recent advancements in intelligent CH selection (CHS) algorithms and QoS- aware RP were systematically reviewed in this study. For CHS and Quality of Service provisioning, 20 state-of-the-art (SOTA) approaches that utilize swarm intelligence (SI), fuzzy logic (FL), machine learning (ML), and hybrid methods are analyzed in this study. When evaluating every technique, the following factors have to be considered: selection strategy, routing efficiency, flexibility, scalability, and the impact on important QoS metrics like packet delivery ratio (PDR), throughput (THRPT), and delay (D). Researchers focus on future initiatives to improve network functionality, security, efficiency, and comparative performance analysis. This study also highlights the research gaps, and it may guide the future studies in the development of more robust and intelligent VANET architecture