## 1 Introduction  
Intelligent transportation systems (ITSs) are garnering increasing attention globally due to the proliferation of vehicles and the emergence of various issues such as traffic congestion, air pollution, and traffic accidents. ITS integrates wireless and advanced IT technologies into mobile vehicles to enhance traffic safety and driver convenience. IEEE has introduced a new wireless communication standard called wireless access in vehicular environment (WAVE), based on IEEE 802.11p, to deliver these services. Consequently, research on vehicular ad-hoc networks (VANETs) is becoming increasingly active [1, 2]. VANETs represent a next-generation network technology that facilitates vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications and is a subclass concept of traditional mobile ad-hoc networks (MANETs). MANETs can establish independent ad-hoc networks among mobile nodes to construct autonomous networks. However, due to the mobile nodes' limited characteristics, such as low bandwidth, low power, and limited resources, MANETs have limitations in realizing various services. In contrast, VANETs can support a broad spectrum of applications as vehicles are equipped with onboard units (OBUs) capable of robust processing without power limitations. These applications include safety measures like vehicle collision avoidance, emergency message dissemination, and traffic accident notification; driver convenience features like alternative route guidance, parking lot location, and gas station payment; and entertainment offerings such as games, movies, and music [3, 4]. In VANETs, multi-hop routing protocols are crucial for supporting application services via wireless communication between vehicles. While various dynamic routing protocols for mobile networks have been proposed in existing MANET research [5; 6; 7; 8], these protocols are unsuitable for VANETs. Designing a routing protocol for vehicular networks poses several challenges. Vehicles move rapidly, leading to frequent topology changes and network link breaks. Moreover, real-time variations in link quality occur based on vehicular traffic density. For instance, low traffic density results in higher packet delay due to fewer vehicles being available to relay packets, whereas high traffic density leads to lower packet delay. Urban environments can exacerbate these challenges by causing packet loss due to obstacles like tall skyscrapers interfering with radio signals. Therefore, vehicular routing protocols must address these demanding conditions diligently. Greedy perimeter stateless routing (GPSR) stands out as a geographically based routing protocol deemed highly suitable for VANETs. It leverages GPS to identify nearby neighbors and employs greedy forwarding to direct packets to the node closest to the destination. GPSR is recognized for its speed, adaptability, and scalability, facilitated by its maintenance of a one-hop neighbor table. However, GPSR is primarily designed for highway scenarios, so it encounters frequent communication drops and high packet latency in urban scenarios [9]. Map-based geographic source routing (GSR) represents a junction-based geographic routing protocol that combines geographic-based (GPSR) and topology-based (DSR) protocols [10]. This method employs the vehicle's digital map to establish a fixed sequence of junctions for routing packets to their destination. However, the junction sequence prioritizes the shortest distance to the destination, neglecting the traffic density through which the packets traverse. Conversely, the enhanced greedy traffic-aware routing protocol (GyTAR) integrates traffic awareness into the existing GSR protocol, introducing a junction-based geographic routing protocol [11]. GyTAR dynamically selects one junction at a time as traffic conditions evolve. The criterion for junction selection is based on the junction's highest density of vehicle traffic and shortest distance to the destination among neighboring junctions.