  Enabling secure and reliable high-bandwidth lowlatency connectivity between
automated vehicles and external servers, intelligent infrastructure, and other
road users is a central step in making fully automated driving possible. The
availability of data interfaces, which allow this kind of connectivity, has the
potential to distinguish artificial agents' capabilities in connected,
cooperative, and automated mobility systems from the capabilities of human
operators, who do not possess such interfaces. Connected agents can for example
share data to build collective environment models, plan collective behavior,
and learn collectively from the shared data that is centrally combined. This
paper presents multiple solutions that allow connected entities to exchange
data. In particular, we propose a new universal communication interface which
uses the Message Queuing Telemetry Transport (MQTT) protocol to connect agents
running the Robot Operating System (ROS). Our work integrates methods to assess
the connection quality in the form of various key performance indicators in
real-time. We compare a variety of approaches that provide the connectivity
necessary for the exemplary use case of edge-cloud lidar object detection in a
5G network. We show that the mean latency between the availability of
vehicle-based sensor measurements and the reception of a corresponding object
list from the edge-cloud is below 87 ms. All implemented solutions are made
open-source and free to use. Source code is available at
https://github.com/ika-rwth-aachen/ros-v2x-benchmarking-suite.
