Expolynomial Modelling for Supporting VANET Infrastructure Planning

The deployment of Intelligent Transportation Systems (ITS) is a challenge for industry and scientific community. Traffic characteristics change widely within a single day, therefore, ITS engineers and researchers must deal with that dynamic behavior. On the other hand, once the ITS depends on networking services, specific studies are required to consider the communication parameters along with vehicle mobility. In this paper, we propose an analytical model based on the Stochastic Petri Net (SPN) theory for evaluating Vehicular Ad-Hoc Networks (VANETs) infrastructures, considering mobility and network parameters, and the respective constraints. We employ expolynomial distributions to represent Roadside Unit (RSU) service rates. Those probability distributions allow the approximation of many analytical and empirical data. Results show that parameters such as vehicular density, message frequency, and RSU radius may affect significantly the overall system performance.