Simulation offers advantages throughout the development process of automated driving functions, both in research and product development. Common open-source simulators like CARLA are extensively used in training, evaluation, and software-in-the-loop testing of new automated driving algorithms. However, the CARLA simulator lacks an evaluation where research and automated driving vehicles are simulated with their entire sensor and actuation stack in real time. The goal of this work is therefore to create a simulation framework for testing the automation software on its dedicated hardware and identifying its limits. Achieving this goal would greatly benefit the open-source development workflow of automated driving functions, designating CARLA as a consistent evaluation tool along the entire development process. To achieve this goal, in a first step, requirements are derived, and a simulation architecture is specified and implemented. Based on the formulated requirements, the proposed vEDGAR software is evaluated, resulting in a final conclusion on the applicability of CARLA for HiL testing of automated vehicles. The tool is available open source: Modified CARLA fork: https://github.com/TUMFTM/carla, vEDGAR Framework: https://github.com/TUMFTM/vEDGAR
翻译:在自动驾驶功能的研究与产品开发过程中,仿真技术在整个开发流程中具有显著优势。诸如CARLA等常用开源仿真器已广泛应用于新型自动驾驶算法的训练、评估与软件在环测试。然而,CARLA仿真器目前缺乏对研究型自动驾驶车辆进行完整传感器与执行器堆栈实时仿真的评估能力。因此,本研究旨在构建一个仿真框架,用于在专用硬件上测试自动驾驶软件并识别其性能边界。实现该目标将极大促进自动驾驶功能开源开发流程的优化,使CARLA成为贯穿整个开发流程的一致性评估工具。为实现此目标,本研究首先推导了系统需求,设计并实现了仿真架构。基于所制定的需求,对提出的vEDGAR软件进行了评估,最终得出关于CARLA在自动驾驶车辆硬件在环测试中适用性的结论。本工具已开源发布:修改版CARLA分支:https://github.com/TUMFTM/carla,vEDGAR框架:https://github.com/TUMFTM/vEDGAR