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Enabling secure and reliable high-bandwidth lowlatency connectivity betweenautomated vehicles and external servers, intelligent infrastructure, and otherroad users is a central step in making fully automated driving possible. Theavailability of data interfaces, which allow this kind of connectivity, has thepotential to distinguish artificial agents' capabilities in connected,cooperative, and automated mobility systems from the capabilities of humanoperators, who do not possess such interfaces. Connected agents can for exampleshare data to build collective environment models, plan collective behavior,and learn collectively from the shared data that is centrally combined. Thispaper presents multiple solutions that allow connected entities to exchangedata. In particular, we propose a new universal communication interface whichuses the Message Queuing Telemetry Transport (MQTT) protocol to connect agentsrunning the Robot Operating System (ROS). Our work integrates methods to assessthe connection quality in the form of various key performance indicators inreal-time. We compare a variety of approaches that provide the connectivitynecessary for the exemplary use case of edge-cloud lidar object detection in a5G network. We show that the mean latency between the availability ofvehicle-based sensor measurements and the reception of a corresponding objectlist from the edge-cloud is below 87 ms. All implemented solutions are madeopen-source and free to use. Source code is available athttps://github.com/ika-rwth-aachen/ros-v2x-benchmarking-suite.

Enabling Connectivity for Automated Mobility: A Novel MQTT-based Interface Evaluated in a 5G Case Study on Edge-Cloud Lidar Object Detection