Data Dissemination in Cooperative ITS from an Information-Centric Perspective

Abstract

The success of cooperative Intelligent Transportation Systems (ITS) applications such as collision avoidance or adaptive cruise control stands or falls with the exchange of information between distributed and usually moving nodes. The extensive transmission of information contrasts with a limited channel bandwidth which has to be shared between all nodes. Thus, a tradeoff is required which cooperatively selects pieces of information for dissemination according to their worth for the receivers under consideration of the communication channel conditions. The tradeoff is achieved by an entropy-based evaluation of evidence in a dynamic probabilistic filter system. With this approach the dissemination priority is based on the uncertainty reduction which can be achieved by the reception of a piece of evidence in contrast to a pure prediction. The novelty of the approach as presented in this paper is exceptional due to its information-centric evaluation of the worth of evidence which has not been performed so far for cooperative ITS applications. It outperforms current state of the art by its generic and theoretically grounded approach for diverse applications, its inclusion of measurement uncertainty, its context-adaptability and its optimized cooperative radio bandwidth utilization.