Rating the Surrounding Vehicle-to-Everything Field, Based on Channel Utilization and Information Influence
by Christoph Pilz (University of Technology Graz, Austria, Virtual Vehicle Research GmbH, Austria), Lukas Kuschnig (Virtual Vehicle Research GmbH, Austria), Alina Steinberger (University of Technology Graz, Austria, Virtual Vehicle Research GmbH, Austria), Peter Sammer (Virtual Vehicle Research GmbH, Austria), Esa Piri (Kaitotek Oy, Finland),Christophe Couturier (YoGoKo, France), Thomas Neumayr (Virtual Vehicle Research GmbH, Austria), Markus Schratter (University of Technology Graz, Austria, Virtual Vehicle Research GmbH, Austria), and Gerald Steinbauer-Wagner (University of Technology Graz, Austria).
Abstract
Automated vehicles (AVs) can get additional information from infrastructure and other vehicles via vehicle-to-everything (V2X) communication. However, how can an AV decide if the surrounding V2X field can reliably provide qualitative, relevant, and trustworthy information? Related research analyzes V2X performance from various angles. However, not only are there identified open gaps in the analysis of loaded channels, but there has also not yet been an effort to design a lightweight metric for rating the quality of the surrounding V2X field. Hence, this work aims to close this existing performance measurement gap and develop a metric for rating the quality of the surrounding V2X field. This article first highlights the gaps identified in performance analysis before closing them with a dedicated measurement campaign. Next, it combines these findings with related research to design a straightforward V2X field rating metric. The resulting V2X field rating metric is a starting point for the AD system to decide if sensor information from the V2X field should be directly incorporated or handled with care.