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.
翻译:使自动化车辆和外部服务器、智能基础设施和其他道路使用者之间能够安全可靠地高带宽低的低频连接,是使完全自动化驾驶成为可能的一个核心步骤。数据接口的可用性使这种连接能够将人造代理人在连接、合作和自动移动系统方面的能力与不拥有这种接口的操作者的能力区分开来。连接的代理商可以分享数据,以建立集体环境模型,规划集体行为,并集体地从中央合并的共享数据中学习。本文提出了多种解决方案,使相连接的实体能够交换数据。特别是,我们提出了一个新的通用通信界面,利用信息叫声遥测距传输(MQTTT)协议连接运行机器人操作系统(ROS)的代理商。我们的工作综合了各种方法,以实时各种关键性能指标的形式评估连接质量。我们比较了各种办法,这些办法为在5G网络中示范性地使用精锐利达尔天文天文天体探测软件提供了必要的连接性。我们显示,在基于车辆的感官测量方法的可用度与基于87clex的传感器测量/端端端端端端端对准软件的接收了所有可使用的源代码。