# A Review of Vehicle to Vehicle Communication Protocols for VANETs in the Urban Environment
## 3 Position-Based Routing in Vehicular Networks
The major problem associated with this routing is that it selects junctions based on directional density and ignores non-directional density flows on a multi-lane road. If directional density is absent then this protocol cannot find the way to relay packets towards the destination. The non-directional density is also useful in relaying packet towards destination [19]. Figure 8: GPCR Inefficiency. Traffic Flow Oriented Routing Protocol (TFOR) [2] is a recently proposed protocol for the urban environment. Its main feature is to assume traffic flows while routing. It consists of two modules: (a) A junction selection mechanism based on traffic flows and the shortest routing path and (b) forwarding strategy based on two-hop neighbor information. While accomplishing the shortest path, it considers traffic flows. It relays the packet from source to destination through those city streets that contain high traffic flows. Higher traffic flows provide more connectivity which increases the throughput of the network. The simulation outcomes, in realistic vehicular traffic urban surroundings, illustrated that TFOR outperforms E-GyTAR, GSR, and GPSR in terms of packet delivery ratio and end-to-end delay. Figure 9 shows the junction selection mechanism of TFOR. In this figure, the source vehicle S that is located at the current junction has two candidate neighbor junctions J\({}_{2}\) and J\({}_{3}\) of the current junction. The traffic flow between the current junctions and J\({}_{2}\) is higher as compared to current junction and J\({}_{3}\). Also, J\({}_{2}\) is at the shortest distance to the destination as compared to J\({}_{3}\). So, TFOR protocol chooses J\({}_{2}\) and moves packet through it towards destination D.  
Directional Geographic Source Routing (DGSR) [19] is an enhanced version of geographic source routing (GSR) with directional forwarding strategy. In this routing protocol, the source node uses location services to get the position of the destination node. It computes the shortest path from the source to destination using Dijkstra Algorithm. The shortest path is composed of a sequence of junctions. The packets from source node follow the sequence of junctions to reach the destination. If packet meets local optimum, DGSR uses carry and forward approach to overcome a local optimum problem. Enhance Greedy Traffic Aware Routing-Directional (E-GyTARD) [19] is an enhanced version of E-GyTAR [8] with directional forwarding. It consists of two mechanisms: (i) Junction selection; (ii) Directional greedy forwarding strategy. It uses location services to get the position of the destination node. It selects junctions on the basis of directional traffic density and shortest distance to the destination. It forwards the packets in between junction using directional greedy forwarding. Simulation outcomes in realistic urban scenarios show that E-GyTARD outperformed GSR and DGSR in terms of packet delivery ratio and end-to-end delay. Table 2 shows the comparative characteristic of all the aforementioned routing protocols. Figure 9: Junction Selection Method in Traffic Flow Oriented Routing Protocol TFOR.