This article introduces an advanced methodology to overcome scalability challenges in Vehicular Ad Hoc Networks (VANETs) by leveraging a high-modularity score to identify and structure community formations more effectively. It emphasizes that in low-modularity communities, selecting a cluster head solely based on node degree often results in suboptimal communication performance and network instability. To address this issue, the proposed approach modularity score for optimized cluster head selection incorporates critical factors such as relative speed, movement direction, and estimated time to leave the communication range. By integrating these parameters, the method ensures a more stable and efficient cluster head selection process, optimizing network organization and enhancing overall communication reliability in VANET environments. This method significantly improves network stability, increases data throughput, and reduces packet delay, making it highly suitable for Vehicular Ad Hoc Networks (VANETs), particularly in densely populated traffic scenarios. By ensuring more reliable and efficient data transmission, it enhances the overall performance of vehicular communication systems, contributing to the development of intelligent transportation solutions in smart city environments.