A HYBRIDIZATION OF ARTIFICIAL NEURAL NETWORK AND SUPPORT VECTOR MACHINE FOR PREVENTION OF ROAD ACCIDENTS IN VANET

Vehicular Ad hoc Network (VANET) is known as an infrastructure less network having dynamic nodes with Road Side Units (RSUs). Data Broadcasting becomes a very difficult task because of more density, scalability, randomness, mobility of vehicles. VANET has an ability to prevent accidents by transmitting data on-time on the network and this has raised an attention for number of researchers. Therefore, in this paper a realistic mechanism has been proposed to avoid the fatal accidents on road using clustering approach with the concept of Artificial Intelligence. Hybridization of Artificial Neural Network (ANN) and Support Vector Machine (SVM) is conducted to speed up the data transmission process that assists in providing information accurately and on-time. To demonstrate the efficacy of the novel mechanism, parameters such as Throughput, Packet Delivery ratio (PDR) are considered.