An adjusted propagation model for ITS-G5 communications for improving the location of RSUs in real V2I deployments

Abstract

The future of mobility is cooperative, connected, and autonomous leading to new technological challenges in the development of Cooperative Intelligent Transport Systems (C-ITS). Therefore, Vehicle to Everything (V2X) and, more specifically, Vehicle to Infrastructure (V2I) deployments are key to enabling these features around the highways as well as along the cities. The communication range of the RoadSide Units (RSUs) is one of the most important aspects when implementing Vehicle-to-Infrastructure (V2I) communications as it has a direct impact on efficiency and the economy of the installation. The aim is to maximise the communication range with the minimum number of RSUs and to optimise the deployments, thus having a realistic simulation tool is key. To be realistic, simulations rely on adequate propagation models, which ideally would adapt to the environment without a high computational need. Therefore, an appropriate characterisation of the different V2X environments as well as a simple and versatile propagation model is an important instrument for deciding the location of the RSUs. In this paper, we characterise different environments for ITS-G5 communications and provide an adjusted propagation model with an α parameter that depends on the environment. Thus, eradicating the need to model the environment and the obstacles in it. For that purpose, a methodology for the modeling and characterisation of the ITS-G5 propagation model is proposed,after that the methodology is applied and the results validated. The methodology is presented and the characterisation of the ITS-G5 environments is made. Later, tests were carried out in different environments to measure how the signal power decreases with the distance. After that, the propagation model for ITS-G5 communications, specifically V2I communications, is presented along with the methodology applied to obtain it. Then, an α value is assigned to each environment. Finally, the validation is made by comparing our adjusted propagation model with other propagation models and applying the adjusted propagation model to a new RSU installation.