Recent research in intelligent routing protocols for Vehicular Ad Hoc Networks focuses on leveraging artificial intelligence, machine learning, and bio-inspired algorithms to optimize route discovery, selection, and maintenance in dynamic vehicular environments. These protocols utilize context-aware decision-making, mobility prediction, and real-time traffic analysis to ensure reliable data transmission with minimal delay and packet loss. Techniques such as neural networks, reinforcement learning, and hybrid swarm intelligence models are being integrated to enhance adaptability and scalability under varying network conditions. Additionally, researchers are incorporating fog and edge computing for faster data processing and blockchain for secure route validation. Overall, intelligent routing in VANETs aims to provide efficient, secure, and autonomous communication frameworks that support intelligent transportation systems and next-generation smart mobility applications.