Cooperative relative localization using Vehicle-To-Vehicle communications

The estimation of a vehicle's dynamic state is one of the most fundamental data fusion tasks for intelligent transportation systems. This paper presents a decentralized data fusion system, which estimates the relative position between traffic participants. For that, GPS pseudorange measurements and ego motion estimations are exchanged by vehicle-to-vehicle communications and incorporated by a relative motion model. Particle filtering is used for the tight coupled relative GPS/INS integration.