Recent research in bio-inspired routing for VANETs is leveraging nature-inspired optimization and swarm intelligence techniques—such as artificial bee colony (ABC), whale optimization, ant colony optimization (ACO) and hybrid metaheuristics—to address the unique challenges of dynamic vehicular networks including high mobility, frequent link breaks and rapidly changing topology. These algorithms are applied to cluster formation, relay selection, path discovery and load balancing to improve packet-delivery ratio, reduce end-to-end delay, minimize routing overhead and enhance network stability. For example, a recent study uses a probabilistic whale-optimization algorithm (p-WOA) for cluster head selection in VANET routing, achieving significantly better throughput and lower latency compared to Ant Lion Optimizer and Grey Wolf Optimizer. Other works hybridize greedy forwarding with bee-colony heuristics under SDN-enabled vehicular frameworks to reduce delays and increase packet delivery in V2V/V2I communications. These bio-inspired approaches show promising results for making routing in vehicular networks more adaptive, efficient and resilient in highly mobile smart-mobility scenarios.