@article{ref1,
title="Edge-based collision avoidance for vehicles and vulnerable users: an architecture based on MEC",
journal="IEEE vehicular technology magazine",
year="2020",
author="Malinverno, Marco and Avino, Giuseppe and Casetti, Claudio and Chiasserini, Carla Fabiana and Malandrino, Francesco and Scarpina, Salvatore",
volume="15",
number="1",
pages="27-35",
abstract="Collision avoidance, one of the most promising applications for vehicular networks, dramatically improves the safety of vehicles that support it. In this article, we investigate how it can be extended to benefit vulnerable users, such as pedestrians and bicyclists, equipped with a smartphone. Owing to the reduced capabilities of smartphones compared to vehicular onboard units (OBUs), traditional distributed approaches are not viable, and multi-access edge computing (MEC) support is needed. Thus, we propose an MECbased collision-avoidance system, discuss its architecture, and evaluate its performance. We find that, thanks to MEC, we are able to extend to vulnerable users the collision avoidance protection traditionally applied to vehicles, without impacting its effectiveness or latency.<p /> <p>Language: en</p>",
language="en",
issn="1556-6072",
doi="10.1109/MVT.2019.2953770",
url="http://dx.doi.org/10.1109/MVT.2019.2953770"
}