Should I Really Care of That CAM?

Most of the applications envisaged for the forthcoming connected vehicles are based on the broadcasting by each vehicle of periodic messages describing its characteristics, state, and actions. Such messages are denoted as cooperative awareness messages (CAMs) in the ETSI standardization. From a communication perspective, the success of CAM delivery is thus a particularly important aspect to evaluate and the obvious method to address large scale scenarios consists in performing simulations. Normally, given that the relevance of the information is related to the distance between communicating vehicles, output metrics are restricted to a given range. However, no attention is typically posed on the relative positions and movements of the vehicles, which could be, for example, on parallel roads. In this work, we propose a novel method to identify and neglect those transmissions that are not really meaningful, based only on the position and direction of the vehicles. Particular emphasis is laid on the efficiency of the methodology for possible large-scale simulations. The described approach is evaluated in a complex urban scenario, where hundreds of vehicles are equipped with either LTE-V2V or IEEE 802.11p. Results show that, in the considered cases, even less than half of the transmissions could be meaningful and that neglecting those that are not relevant significantly impacts on the quality of the investigated application.