Increasing interests in Vehicular Ad hoc NETworks (VANETs) over the last decade have led to huge investments in technologies and research to improve road safety by providing timely and accurate information to drivers and authorities. To achieve the timely dissemination of messages, various routing protocols for VANETs have been recently proposed. We present a Hybrid Bee swarm Routing (HyBR) protocol for VANETs. HyBR is based on the continuous learning paradigm in order to take into account the dynamic environmental changes in real-time which constitute a key property of VANETs. The protocol combines the features of topology routing with those of geographic routing. HyBR is a unicast and a multipath routing protocol (aimed at both urban and rural scenarios) which guarantees road safety services by transmitting packets with minimum delays and high packet delivery. To demonstrate the effectiveness and the performance of HyBR, we conducted a performance evaluation based on several metrics such as end-to-end delay, packet delivery ratio, and normalized overhead load. We obtained better performance results with HyBR in contrast to results obtained from traditional routing algorithms such as Ad hoc On-Demand Distance Vector (AODV) topology-based routing protocol and Greedy Perimeter Stateless Routing (GPSR) geography-based protocol.