Cooperative automated vehicles can exchange information to assist each other in creating a more precise and extended view of their surroundings, with the aim of improving automated-driving decisions. This project addresses the need for scalable communication among these vehicles. To this end, a general communication framework is proposed through which automated cars exchange information derived from multi-resolution maps created using their local sensing modalities. This method can extend the region visible to a car beyond the area directly sensed by its own sensors. An adaptive, probabilistic, distance-dependent strategy is proposed in our recent work (see the list of papers below) that controls the content of the messages exchanged among vehicles based on performance measures associated with the load on the communication channel.