Recent research in the applications of game theory in vehicular networks explores strategic decision-making frameworks to enhance communication efficiency, resource allocation, and security in highly dynamic vehicular environments. Game-theoretic models such as non-cooperative, cooperative, evolutionary, and Stackelberg games have been widely applied to optimize spectrum sharing, routing, congestion control, and incentive mechanisms for data dissemination. Recent studies also focus on integrating game theory with machine learning and blockchain to enable decentralized and adaptive solutions for trust management, intrusion detection, and privacy preservation. These approaches not only ensure fairness and stability among participating vehicles but also significantly improve overall network performance and reliability in Internet of Vehicles (IoV) and 6G-enabled vehicular systems.