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Intersections are critical areas of the transportation infrastructureassociated with 47% of all road accidents. Vehicle-to-vehicle (V2V)communication has the potential of preventing up to 35% of such serious roadcollisions. In fact, under the 5G/LTE Rel.15+ standardization, V2V is acritical use-case not only for the purpose of enhancing road safety, but alsofor enabling traffic efficiency in modern smart cities. Under this anticipated5G definition, high reliability of 0. is expected for semi-autonomousvehicles (i.e., driver-in-the-loop). As a consequence, there is a need toassess the reliability, especially for accident-prone areas, such asintersections. We unpack traditional average V2V reliability in order toquantify its related fine-grained V2V reliability. Contrary to existing work oninfinitely large roads, when we consider finite road segments of significanceto practical real-world deployment, fine-grained reliability exhibits bimodalbehavior. Performance for a certain vehicular traffic scenario is either veryreliable or extremely unreliable, but nowhere in relative proximity to theaverage performance.

Fine-Grained vs. Average Reliability for V2V Communications around Intersections