## 2 Related Work
### Traffic-Aware Routing Protocols  
Since network performance in VANETs is highly dependent on vehicle traffic density, routing protocols that include junction selection techniques that take traffic density into account are essential. Previous works [24; 25; 26; 27] proposed an optimal junction selection technique that considers traffic conditions at junctions. This technique uses fog nodes in the RSU to collect traffic information to select the optimal junction considering traffic flow,  
Figure 1: The need for junction-based routing protocol in urban environments.  
traffic density, and vehicle speed. However, this technique can have a devastating impact on delay-sensitive applications as the traffic bandwidth of the RSUs rapidly decreases as the number of vehicles around the intersection increases. Furthermore, the need to deploy RSUs at each junction is cost prohibitive. In [11], a traffic-aware optimal junction selection technique based on traffic awareness was proposed by collecting vehicle information without the help of RSUs in a vehicular ad-hoc environment. This approach circumvents the selection of junctions (anchors) because even if the distance to the destination is close, the network will perform poorly on roads with low vehicle traffic density. Conversely, it acknowledges that roads with high vehicular traffic density exhibit superior network performance, thus opting for those junctions to forward packets to the destination [20; 28].  
Anchor-based street- and traffic-aware routing (A-Star) [29] is a traffic-aware routing protocol that leverages city bus routing data. The rationale is to utilize city bus routes to determine the sequence of junctions (anchors) since these routes typically experience high vehicle traffic density. However, as this technique solely focuses on traffic density, the resulting routing path may not be optimal.  
GyTAR [11] dynamically selects a junction by considering the optimal distance and traffic density for packets to reach their destination. GyTAR employs the infrastructure free-traffic information system (IFITS) to estimate traffic density between junctions without relying on fixed infrastructure such as RSUs. The forwarding vehicle utilizes the navigation system's road map to locate neighboring junctions. For each candidate neighborhood junction, the forwarding vehicle computes the shortest distance to the destination [30] and assigns a score based on vehicle traffic density weight. Subsequently, the junction with the highest score among the candidate neighboring junctions is selected as the next neighbor junction, and the packet is forwarded. Suppose a forwarding node encounters a local maximum between junctions. In that case, it employs a recovery mode by executing \"carry and forward\" [31], where packets are stored in a buffer and forwarded upon encountering a nearby vehicle or reaching the next junction. However, as this protocol only considers traffic density for the first neighboring junction, the traffic density between the next two neighboring junctions remains unpredictable. In other words, the subsequent selection of the second neighboring junction may occasionally encompass roads without vehicular traffic. Ultimately, this scenario can result in a diminished packet delivery ratio due to packet loss or increased end-to-end delay stemming from frequent recovery strategies. The following Table 1 describes the characteristics and comparison of MJTAR proposed in this work and previously proposed vehicular routing protocols.