Abstract
Abstract Vehicle to vehicle (V2V) communications have been widely employed to ameliorate a variety of transportation-related issues in cities, the most significant of which being traffic congestion. The inefficient utilization of resources in vehicle infrastructure is frequently the source of a great deal of traffic congestion. Furthermore, due to its high dynamic nature, incorporating traffic congestion into vehicular traffic decision-making is difficult. In this paper, V2V communications will be implemented as an intelligent transportation systems (ITS) safety mechanism solution to solve these traffic congestion problems. The proposed mechanism is applied over integration between AODV (Ad hoc On-Demand Distance Vector) as one of the best topology-based routing protocols with one of geographic-based routing protocols to overcome OADV limitations. As AODV floods the network with control messages to find a path to the target, and the network is going to host a high volume of control packets. So the proposed method will use Global Positioning System (GPS) coordinates to search the region where a path to the target is likely to be found. As this paper describes the efforts to create a hybrid model that combines a typical reactive routing protocol with a geographic one, there will be two steps to identify the proposed ITS network. In first Phase: Choose the most functioning Geographic routing protocol on the V2V simulation environment. In the second Phase: Integrate this suggested Geographic routing protocol with ADOV protocol to implement ITS architectures. The RIVERBED modulator and NS2 simulator will be utilized to choose the best routing protocol. Based on the paper’s key performance indicators simulation results, Distance-Vector-Based Recovery-Strategy (PBR-DV) geographic routing protocol is selected to integrate with AODV routing protocol. Comparing the proposed method with the independent use of AODV, it demonstrated the effectiveness of the proposed method in overcoming all the problems related to resource scarcity and geographical obstacles.
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More From: International Journal on Smart Sensing and Intelligent Systems
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