Modelling the Impact of 5G NR-V2X Message Losses on the Behaviour of Connected Automated Vehicles

The behaviour of connected automated vehicles in implementing cooperative safety functions depends on the timely exchange of V2X messages. At the same time, the end-to-end impact of 5G NR-V2X Mode 2 message delivery failures on vehicle behaviour requires evaluation not only by aggregated network metrics but also by the timeliness of V2X message arrival within the time window acceptable for the control controller. The paper presents a reproducible co-simulation environment integrating the SUMO traffic mobility simulator, information exchange via TraCI, network simulation in ns‑3/ms-van3t, the 5G-LENA NR sidelink module, the Sionna RT geometric radio channel model and event logs. The environment implements mechanisms for modifying link quality for individual vehicles and end-to-end message tracing with identifier preservation for message analysis and assessment of the impact of message losses on connected automated vehicle behaviour. Experimental validation was performed in two scenarios. In the emergency vehicle warning scenario, a series of 140 independent iterations showed that as PRR (Packet Reception Ratio) decreases from 0.9412 to 0.0675, the 90th percentile of the first CAM (Cooperative Awareness Message) reception delay increases from 4.45 to 32.52 s. Spearman’s rank correlation identifies a direct relationship between txPower (transmitter power) and PRR (ρs = 0.981, p < 0.001) and an inverse relationship between PRR and P90 delay (ρs = –0.927, p < 0.001). In the priority intersection conflict scenario, stable V2X message exchange ensures that the first useful warning arrives before the critical moment of control action formation. As a result, no collision occurred in any of the 30 independent iterations. In the “radar-only” and “radar + degraded V2X” modes, the warning arrives after the critical moment, causing each iteration to end in a collision. The results show that the safety assessment of cooperative functions requires joint analysis of PRR, the temporal structure of message arrival and vehicle behaviour.

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