Feasibility Assessment of Remote Driving via Latency Analysis of ITS-G5 and Cellular Networks in the MASA Living Lab

2026-06-11

AI Summary

This study addresses the critical challenge of deploying remote driving, which hinges on wireless networks delivering low and predictable end-to-end latency. Leveraging MASA—a city-scale real-world testbed—this work presents the first systematic comparison between ITS-G5 and 5G in an operational intelligent transportation infrastructure, evaluating uplink video streaming and downlink control command latency and reliability under varying network loads and traffic conditions. The findings reveal fundamental differences in latency and its variability between the two technologies, quantify the impact of infrastructure coverage on video transmission quality, and inform the design of a hybrid communication strategy. This approach significantly enhances the feasibility and safety of remote driving, offering actionable guidance for network selection and integration in future deployments.

Abstract

Remote driving has gained increasing attention as a key enabler for connected and automated vehicles. Yet its practical deployment hinges on wireless networks' ability to guarantee low, predictable latency. In this paper, we present an extensive latency analysis of ITS-G5 and cellular (5G) technologies within the Modena Automotive Smart Area (MASA), a real-world, city-scale testbed equipped with a distributed intelligent transportation infrastructure. By conducting controlled experiments under varying network loads and traffic conditions, we measure network and end-to-end latency components relevant to remote driving, in which the uplink consists of a continuous video stream transmitted from the vehicle to the remote operator, and the downlink conveys control commands back to the car. Measurements conducted under diverse conditions reveal how latency and variability differ across the two technologies and how infrastructure coverage impacts video-stream transmission performance. Based on the observed latency distributions and reliability metrics, we assess the practical feasibility and safety margins of remote driving in mixed network environments. The results provide actionable insights for future teleoperation deployments and motivate hybrid communication strategies that combine the strengths of ITS-G5 and cellular networks.

Problem

• remote driving
• latency
• ITS-G5
• cellular networks
• feasibility assessment

Innovation

• remote driving
• latency analysis
• ITS-G5
• 5G cellular networks
• hybrid communication