A Kalman Filter Based Hybrid Routing Protocol for Efficient Vehicle Connectivity and Traffic Management

The geographic routing protocols in Vehicular Ad Hoc Networks (VANETs) are contemplated as most efficacious protocols. Though, such types of protocols communicate a huge quantity of data that influence the network connectivity negatively. Also, out of bound issue is the second major disadvantage of geographic routing protocols. To provide a solution to these impediments, a novel K-PGRP (Kalman filter-Predictive Geographic Routing Protocol) routing protocol is proposed in this paper. K-PGRP is an improvement to PGRP (Predictive Geographic Routing Protocol) routing protocol and wields Kalman filter as a prediction module in PGRP routing protocol in order to anticipate the neighbor location and to select the propitious neighbor for advancing packets in both urban and highway framework which leads to efficient connectivity in the network and improves road safety. K-PGRP is then compared with PGRP, GPSR (Greedy Perimeter Stateless Routing) and GPCR (Greedy Perimeter Coordinator Routing) routing protocols in terms of throughput and packet delivery ratio metrics and outperformed all the simulation cases. The simulations were performed on MATLAB R2018a along with traffic simulator SUMO.