Onboard perception systems found on modern vehicles generate data that are incredibly rich in contextual information, and thanks to the increasing number of vehicles equipped with communication capabilities, the valuable data generated can be shared with nearby vehicles. One of the most studied vehicular applications for autonomous driving is platooning, for which all maneuvers are managed by the Platoon Leader (PL) with the aid of context information available through Vehicle-to-Vehicle (V2V) messages. However, redundant context information from nearby vehicles in the platoon creates an additional workload for the platoon leader resulting in elevated computational costs. To overcome the challenge of redundant context information, the formation of vehicular micro-clouds can offload the platoon leader by enabling vehicles in a cluster to more effectively utilize the available context data through collective data processing and aggregation. The proposed solution, called Platoon Local Dynamic Map (P-LDM), creates a single database of context information, distributing the data aggregation load among all members of the platoon. Simulation results evaluate the collective perception enhancement and the distribution of the computational load, comparing the proposed scheme with usual Cooperative Perception mechanisms.
