Vehicular Communication Strategy Using Machine Learning and Image Processing to Enhance Observations and Control on the Road Side Area

Abstract

AbstractThe Vehicular Communication System (VCS) is a cooperative engagement of Vehicle Nodes with the required intervention of On-Board Unit (OBU), Cluster Head Unit (CHU), Road Side Unit (RSU), and Infrastructure Domain Unit (IDU). These all units provide exceptional performance with the help of Digital Fragment Processing (DFP), Machine Learning (ML), Internet of Things (IoT), and 5G technologies. However, during vehicular communication lot of data is required to transceive. This high volume of data traffic increases the unbearable load at each transceiver node, this increases data transmission delay. The delay affects the reliability of VCS, this needed to be resolved using some enhanced efficient strategy. Therefore a CHUS algorithm has been proposed in this article that follows the CHU strategy. The simulation results show that our proposed strategy algorithm performs better with existing strategies by enhancing the reliability of VCS by reducing average delay.KeywordsVCSVANETVehicle communicationCHUSRSUReliability enhancement