Edge-Based Collision Avoidance for Vehicles and Vulnerable Users: An Architecture Based on MEC

Abstract

Collision avoidance is one of the most promising applications for vehicular networks, dramatically improving the safety of the vehicles that support it. In this paper, we investigate how it can be extended to benefit vulnerable users, e.g., pedestrians and bicycles, equipped with a smartphone. We argue that, owing to the reduced capabilities of smartphones compared to vehicular on-board units, traditional distributed approaches are not viable, and that multi-access edge computing (MEC) support is needed. Thus, we propose a MEC-based collision avoidance system, discussing its architecture and evaluating its performance. We find that, thanks to MEC, we are able to extend the protection of collision avoidance, traditionally thought for vehicles, to vulnerable users without impacting its effectiveness or latency.