Anti-Jamming Vehicle To Vehicle Communication For Intelligent Transport System Using Fuster’s Paradigm

Abstract

Connected and Autonomous Vehicles (CAV) has the ability of sensing its current circumstance and moving securely with practically no human information. The anti-jamming Vehicle to Vehicle (V2V) transmission in CAV networks for Intelligent Transport System (ITS) utilizing fuster's paradigm. Cognitive Dynamic System (CDS) that builds rules of behavior consisting of five principles of human cognition known as Fuster’s paradigm which embodies perception-action cycle (PCA), memory, attention, intelligence, and language. The lane features are obtained from the imagesobtained through feature extraction process. The obtained images through sensors are sampled for object detection. The reinforcement learning of the vehicles environment where the vehicles learn about the existing world and the action. The key optimization process during the simulation is to get the accumulated reward and not just simultaneous reward. The accurate distance between the vehicles and interpretation of the inter-system relationship between radar tracking and vehicular communication is achieved. V2V communication for autonomous vehicles receives messages as a local or global message based on the message received the action taken. Thus, the V2V communications in intelligent transport system achieves average accuracy 97.04% without any loss of communications overcoming the jamming to avoid collision between vehicles.