为自动驾驶赛车系统打造实时3倍加速的自动化仿真与报告工具
Fast and Realistic Automated Scenario Simulations and Reporting for an Autonomous Racing Stack
- 用高保真车辆模型和FMU接口实现快速仿真
- 支持高速超车、定位等关键模块的多条件验证
- 可注入传感器故障，适合团队持续集成测试
本文介绍为自主赛车系统ur.autopilot开发的自动化仿真与报告流水线。核心采用高保真车辆模型，以功能性模拟单元（FMU）形式接口，可在本地或GitHub CI/CD环境中实现软件栈与仿真的运行速度达到真实时间的三倍以上。流水线的核心输入是一组运行场景，每个场景可设置自车在不同初始位置和速度下启动，并配置任意堆栈参数，有效验证高速超车、定位等关键模块。此外，实现了故障注入模块，可引入传感器延迟、扰动及任意节点输出修改。最后设计了自动化报告流程，以最大化仿真分析效率。
原文摘要 · Abstract (English)
In this paper, we describe the automated simulation and reporting pipeline implemented for our autonomous racing stack, ur.autopilot. The backbone of the simulation is based on a high-fidelity model of the vehicle interfaced as a Functional Mockup Unit (FMU). The pipeline can execute the software stack and the simulation up to three times faster than real-time, locally or on GitHub for Continuous Integration/- Continuous Delivery (CI/CD). As the most important input of the pipeline, there is a set of running scenarios. Each scenario allows the initialization of the ego vehicle in different initial conditions (position and speed), as well as the initialization of any other configuration of the stack. This functionality is essential to validate efficiently critical modules, like the one responsible for high-speed overtaking maneuvers or localization, which are among the most challenging aspects of autonomous racing. Moreover, we describe how we implemented a fault injection module, capable of introducing sensor delays and perturbations as well as modifying outputs of any node of the stack. Finally, we describe the design of our automated reporting process, aimed at maximizing the effectiveness of the simulation analysis.
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