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The support for reliable communication in the increasingly large fleets of autonomous vehicles is one of the important challenges for emerging 5G systems. The presence of heterogeneous data streams of different priority between the connected vehicles (coordinated autonomous driving, platooning, passenger entertainment services, etc.) calls for new methods to estimate the performance characteristics of these systems. In this article, a novel mathematical framework is proposed to model the process of dynamic radio resource (re-)allocation across multiple competing data streams in autonomous vehicular fleets equipped with 5G cellular capabilities. The developed framework is subsequently applied to: (i) study the coexistence of multiple traffic types having different service requirements and (ii) quantify the impact of session prioritization schemes. Our study reveals that the prioritization scheme initially offloading high-rate entertainment sessions, named ESpreempt, in most of the setups achieves a 5-30% performance gain in comparison with the scheme initially offloading low-rate platooning sessions, named PSpreempt. It is also shown that higher variations in the traffic load of autonomous driving sessions have a distinctly negative impact on system-level performance. The outlined framework can be applied in a wide range of 5G vehicular scenarios, as well as extended to capture other categories of data streams in future wireless networks.

Session-Level Reliability Analysis for Multi-Service Communication in Autonomous Vehicular Fleets