# Impact of Direction Parameter in Performance of Modified AODV in VANET
## 1 Introduction
In addition, it does not consider other performance matrices, such as throughput and E2E delay, when considering the performance of the proposed method. [PERSON] et al. [7] proposed a global positioning system (GPS)-based AODV (GBAODV) routing protocol to establish a route. They constrained the flooding of AODV routing packets using GPS devices to improve routing performance. They found that their GBAODV method reduces the network load more than the AODV method. As a result, the number of broken links and the packet loss ratio are reduced. The average E2E delay is also shorter when using GBAODV than AODV. However, when they considered different highway scenarios, the performance of the GBAODV method for packet loss was not satisfactory (more than 10%). Their study was also based on a small number of nodes (only eight nodes). [PERSON] et al. [8] incorporated vehicles' movement information into the route discovery process based on an AODV for VANET applications to improve the reliability of the routing protocols (more stable route). They considered the total weight of the route (based on the position metrics) (TWR) and the estimated expiration time in their proposed protocol to achieve more stable routing. They found that their proposed protocol reduces the routing load even more and ensures more stable connections. Nevertheless, their proposed protocol does not show significant improvement in the percentage of packet drops. [PERSON] et al. [9] proposed a new vehicular reliability model that uses vehicle movement information and channel state information to improve the reliability of routing in VANETs. They extended the AODV routing protocol by proposing a reliable ad hoc, on-demand distance vector routing protocol AODV-L. They compared the traditional AODV routing with AODV-L using Objective Modular Network NESTbed in C++ (OMNeT++). They found that the AODV-L routing protocol outperformed the AODV in terms of PDR and E2E delay. Nevertheless, this study only focused on rural highways. [PERSON] et al. [10] suggested fuzzy logic to improve the efficiency of routing protocols in AODV. They used direction, speed, and distance of vehicles to the destination as inputs to a fuzzy logic controller. Their proposed protocol outperformed the original AODV for average E2E and both AODVand FCAR for the packet delivery rate. Nevertheless, the proposed protocol underperformed FCAR regarding the average E2E delay. [PERSON] et al. [11] proposed an efficient message routing framework to optimize the message delivery throughput from vehicles to RSUs. They developed a mathematical model to examine the asymptotic throughput scaling of VANETs. However, the throughput of their method was poor (0.16 packets/sec). To improve the QoS of the vehicular network under different road scenarios (urban, rural, and highway), optimization of performance matrices (i.e., throughput, the percentage of packet loss, E2E delay, and the network coverage) is essential. To increase reliability and resource usage efficiency based on medium access control (MAC) protocol, [PERSON] et al. [12; 13], suggested applying orthogonal frequency division multiple access (OFDMA) for alert message flooding in VANETs. They compared their protocols with other benchmark MAC protocols. In [14], [PERSON] et al. proposed an OFDMA-based efficient cooperative MAC (OEC-MAC) protocol for VANETS. The OEC-MAC protocol ensured an increase in throughput with a delay of 100 ms for safety messages. The network connection reliability was raised by reducing the packet dropped rate. In our study, we modified the AODV routing protocols to include the information on speed, direction, and position of vehicles. The routing tables now include the additional direction information of the nearby vehicles. In [4], [PERSON] et al. used the direction parameter to select the next-hop only.