Vehicular Collaborative Technique for Location Estimate Correction

Awareness of a vehicle's precise location in VANET is vital so that any vehicle can provide accurate data to its peers. Currently, typical localization techniques integrate the GPS receiver data and the measurements of the vehicle's motion. However, when the vehicle passes through an environment that creates multipath signals, these techniques fail to produce the high localization accuracy that they attain in open environments. The goal of this research is to minimize the multipath effect with respect to the localization accuracy of the vehicles in VANET. The proposed technique, IVCAL, takes advantage of the communications among the VANET vehicles in order to obtain more information from the vehicle's neighbours. The proposed technique integrates all these pieces of information with the vehicle's own data and applies optimization techniques to minimize the error in the location estimate. The simulation results in this paper show a decrease of up to 53% in the location estimate error compared to the error in the traditional techniques.