Centralized services with Vehicle-to-Infrastructure communication can be leveraged to provide precise and up-to-date maneuver recommendations to autonomous vehicles, enabling higher levels of automation. As centralized services have a complete view of the situation on the road, they can be exploited to enable L4 automation & beyond, as opposed to having each node manage an automated maneuver in a distributed way. It is thus pivotal to develop and deploy efficient real-time services, at the edge of the network, to enable low-latency maneuver management services. This paper presents an innovative open-source, 5G & Multi-Access Edge Computing enabled service, called Server Local Dynamic Map (S-LDM), aimed at collecting information about vehicles, based on standard-compliant messages, to create a map of the road, which can then be efficiently shared with other services managing L4 automation. We validated our service on both simulation and pilot trial on a production 5G network involving three main European Mobile Network Operators and real vehicles from Stellantis.


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    Titel :

    S-LDM: Server Local Dynamic Map for Vehicular Enhanced Collective Perception




    Erscheinungsdatum :

    2022-06-01


    Format / Umfang :

    682304 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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