Day 2 V2X applications are the next step in vehicular communications, as they aim
to extend the scope of shared information. In addition to status data, traffic participants
are also aware of each other's sensory capabilities and the data deriving from those
sensors. Collective Perception (CP), one of the flagship Day 2 services, enables vehicles
and infrastructural elements, like roadside units or smart intersection controllers,
to provide information about detected objects, significantly increasing the level
of cooperative awareness V2X can grant for the communicating entities. However, with
the escalation in the amount of data to be sent over the vehicular or mobile networks
and the need for more processing power to enable real-time safety applications based
on CP, some form of infrastructural aid is needed. The traditional central cloud-based
approach might fall short of meeting the latency requirements. To keep latency within
an acceptable range and solve the computational tasks locally, leveraging the capabilities
of 5G Multi-access Edge Computing (MEC) could be a potential solution, thus ensuring
a minimum impact on the core network. The architectural design and the modular approach
of service implementation in the MEC specification by ETSI enable quick service deployment.
This paper focuses on advanced Collective Perception-based V2X applications and the
potential positive impact on their performance when operating with the support of
edge computing. We also present the description – including the design considerations
– of an initial, Artery/Simu5G-based edge service model working as a network-side
intelligence extending the functionality of applications hosted on the vehicles.
