A Topology-Based Approach to the Predictive Analysis of Intelligent Transportation Systems Dynamics

Intelligent Transportation Systems (ITS) refer to the applications of information and communication technologies to the field of transportation. The intelligence of such systems comes from their capacity of sensing, communicating, storing and processing information and adapting their own behavior according to the environment and in order to insure safe and enjoyable driving. In ITS applications the vehicle behavior can adapt in order to control the efficiency of traffic flows, detect traffic incidents, reduce energy consumptions and improve the safety of vehicle, occupants and carried goods. ITS present high dynamic structures where the use of sensors is necessary to collect data upon which decisions will be made and that will have an impact on the topology control of the vehicular network and the behavior of drivers on roads. In recent years, various issues concerning vehicle connectivity and broadcasting messages over such networks have reached a major interest. In order to design effective proactive protocols for such distributed and highly dynamic networks, this paper examines various topology metrics and establishes different iterative schemes to calculate diverse statistical indices that allow us to relate and predict the dynamic environment of a vehicle while traveling.