A vehicular network is an assisting technology that supports many applications. Safety is one of the most crucial among all the applications. Vehicles generally exchange emergency messages through direct communication. But in the real world, this type of communication is not possible to build among vehicles because of obstacles that can be static or dynamic. This situation is normally called non-line of sight. As a researcher, we aim to develop an approach for improving awareness among neighboring vehicles, reducing latency and mean square error rates. In this paper, we describe various methodologies related to vehicular network systems. Deliberation of various techniques with different datasets and corresponding performance metrics for improving the system performance are described here. Keywords: Trajectory, Prediction, Vehicular, VANET.
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