# A Comprehensive Real-Time Traffic Map for Geographic Routing in VANETs
## 2 Related Work  
Vehicular ad hoc networks have a typical problem of intermittent connectivity due to the rapidly changing topology. Many studies have proposed different solutions to deal with this problem. In this section, we survey several significant geographic routing protocols in VANETs and then discuss their pros and cons, as listed in Table 1.  
In [10], the Greedy Perimeter Stateless Routing (GPSR) proposes an early concept of geographic routing based on the positions of the mobile nodes. Each node obtains its geographic position from a GPS receiver, and is aware of its neighbors' positions through periodical beacon messages. The GPSR are divided into two phases: greedy forwarding and perimeter forwarding. In greedy forwarding, an intermediate node selects the neighbor closest to the destination as a next-hop relay node and forwards the data packets to it. This process is repeated until the destination is reached. If there is no closer neighbor than itself, greedy forwarding fails, which is defined as a local maximum problem. Then, perimeter forwarding is triggered as a recovery strategy. The right hand rule is used to find a relay node. Greedy forwarding takes place again if a closer node to the destination is found. The GPSR suffers from a long delivery path in perimeter forwarding and thus encounters a high end-to-end delay. Greedy Perimeter Coordinator Routing (GPCR) [11] adopts the same idea of geographic forwarding and proposes to always forward data packets at junctions. A static road map is used by the GPCR to support the idea and offer data packets a better chance to reach their destination faster. A carry and forward strategy is adopted as the recovery strategy. Once a vehicle cannot find a better relay vehicle, it will carry the data pack until it encounters a better one. However, carry delay is much longer than transmission delay. Road (and/or junction) selections in routing decisions thereby become a critical issue. The improved Greedy Traffic Aware Routing protocol (GyTAR) [21] is an intersection-based geographic routing protocol, which works well in a city environment. It proposed a dynamic junction selection mechanism to support greedy forwarding and to select a more reliable route. GyTAR utilizes IFTIS [18] to estimate the traffic density between two junctions. Vehicles at an intersection forward broadcast a Cell Density Packet (CDP) to collect real-time vehicular density, as shown in Figure 2. In IFTIS, a road segment is divided into fixed-size cells based on the vehicle's communication range. A cell leader is responsible to calculate the number of vehicles in the cell. A CDP is forwarded to each cell leader to collect the traffic density of the cells. Based on this information, GyTAR can decide which junction has the higher traffic density and the shorter distance to the destination. In GyTAR, the direction of the traffic flow is omitted in the next junction selection. Improved Greedy Traffic Aware Routing (E-GyTAR) [22], Traffic Flow-Oriented Routing (TFOR) [23], Intersection-based Connectivity Aware Routing (iCAR) [24], Adaptive Routing Protocol based on QoS and vehicular Density (ARP-QD) [25], and Adaptive QoS based Routing for VANETs