Enhancing Road Safety: A Comparative Study between UAV-Assisted and Autonomous Vehicles
Résumé
The integration of connected autonomous vehicles
(CAV) on open roads has gained significant progress in address-
ing road safety. These vehicles use advanced sensor technology
to perceive and react to the road environment, reducing accident
risks. Despite these advancements, limitations persist in their
perception capabilities. To overcome these limitations, interest
is growing in using Unmanned Aerial Vehicles (UAVs) for
traffic surveillance, offering extensive coverage and enhanced
responsiveness over fixed sensors. In this article, by tackling
an optimization problem in road safety using Particle Swarm
Optimization (PSO), we particularly focus on a situation where
a random flow of vehicles aims to navigate an intersection safely.
We compare two scenarios with and without the assistance of
an UAV: one where vehicles autonomously manage their speed,
and another one where an UAV improve traffic management.
Simulation results underscore the pivotal role of drone-assisted
vehicles in enhancing road safety, compared to sensors embed-
ded within CAVs. Towards the end of the article, we explore
the efficiency of the drone strategy by addressing the issue of
delay in the acceptance and implementation of optimal speed
instructions, comparing scenarios with and without this delay.