Performance Evaluation of V2X Communication Using Large-Scale Traffic Data
John Pravin Arockiasamy, Alexey Vinel
TL;DR
The paper tackles the challenge of assessing V2X performance under realistic, large-scale traffic by leveraging real-world HighD and InD mobility data and simulating V2X communications over them with a standardized ETSI ITS-G5 stack. The authors develop a data-driven pipeline that converts real trajectories into SUMO-compatible representations and enables message-level analysis for populations exceeding 100,000 vehicles across highway and urban intersection settings. They provide population-scale insights into CAM generation, range-dependent reception, and channel load, and show that cooperative awareness remains feasible in real deployment while synthetic traffic can overestimate congestion. The findings suggest that traffic density and mobility patterns critically shape V2X performance and that reactive DCC is rarely activated in real-world-like conditions, informing design and deployment of future V2X systems and congestion-control strategies.
Abstract
Vehicular communication (V2X) technologies are widely regarded as a cornerstone for cooperative and automated driving, yet their large-scale real-world deployment remains limited. As a result, understanding V2X performance under realistic, full-scale traffic conditions continues to be relevant. Most existing performance evaluations rely on synthetic traffic scenarios generated by simulators, which, while useful, may not fully capture the features of real-world traffic. In this paper, we present a large-scale, data-driven evaluation of V2X communication performance using real-world traffic datasets. Vehicle trajectories derived from the Highway Drone (HighD) and Intersection Drone (InD) datasets are converted into simulation-ready formats and coupled with a standardized V2X networking stack to enable message-level performance analysis for entire traffic populations comprising over hundred thousands vehicles across multiple locations. We evaluate key V2X performance indicators, including inter-generation gap, inter-packet gap, packet delivery ratio, and channel busy ratio, across both highway and urban intersection environments. Our results show that cooperative awareness services remain feasible at scale under realistic traffic conditions. In addition, the findings highlight how traffic density, mobility patterns, and communication range influence V2X performance and how synthetic traffic assumptions may overestimate channel congestion.