Inter-vehicle object association for cooperative perception systems

In cooperative perception systems, different vehicles share object data obtained by their local environment perception sensors, like radar or lidar, via wireless communication. Inaccurate self-localizations of the vehicles complicate association of locally perceived objects and objects detected and transmitted by other vehicles. In this paper, a method for inter-vehicle object association is presented. Position and orientation offsets between object lists from different vehicles are estimated by applying point matching algorithms. Different algorithms are analyzed in simulations concerning their robustness and performance. Results with a first implementation of the so-called Auction-ICP algorithm in a real test vehicle validate the simulation results.