Kalman Filter for Local Optimum Problem of Geographic Routing Protocol in VANETs

Abstract

Vehicular communication has diverse set of applications and has procured ubiquity in automotive industry these days. To perpetuate robust communication among vehicles amid progressively changing street topology is one of the difficulties of vehicular communication. Traffic density and its estimated progress information will assist in combating the urban vehicular difficulties. Although geographic routing renders best route selection for vehicles in VANET environment but it has few constraints like Local optimum problem. To resolve this problem, the paper presents a novel approach to predict proper location of vehicle in future wielding Kalman filter. Also, the real world scenario of Bengaluru city is simulated by SUMO tool for VANET network. Thus, Kalman filter precisely estimates the future location of vehicle and assists in proper information dissemination in VANETs wielding MATLAB and SUMO tool together.