Competing with autonomous model vehicles: a software stack for driving in smart city environments

Julius Bächle, Jakob Häringer, Noah Köhler, Kadir-Kaan Özer, Markus Enzweiler, Reiner Marchthaler
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Abstract

This article introduces an open-source software stack designed for autonomous 1:10 scale model vehicles. Initially developed for the Bosch Future Mobility Challenge (BFMC) student competition, this versatile software stack is applicable to a variety of autonomous driving competitions. The stack comprises perception, planning, and control modules, each essential for precise and reliable scene understanding in complex environments such as a miniature smart city in the context of BFMC. Given the limited computing power of model vehicles and the necessity for low-latency real-time applications, the stack is implemented in C++, employs YOLO Version 5 s for environmental perception, and leverages the state-of-the-art Robot Operating System (ROS) for inter-process communication. We believe that this article and the accompanying open-source software will be a valuable resource for future teams participating in autonomous driving student competitions. Our work can serve as a foundational tool for novice teams and a reference for more experienced participants. The code and data are publicly available on GitHub.

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与自动驾驶模型车竞争:智能城市环境中的驾驶软件堆栈
本文介绍了专为 1:10 比例自动驾驶模型车设计的开源软件栈。这款多功能软件堆栈最初是为博世未来交通挑战赛(BFMC)学生竞赛开发的,适用于各种自动驾驶竞赛。该堆栈包括感知、规划和控制模块,每个模块对于在复杂环境(如 BFMC 中的微型智能城市)中精确可靠地理解场景都至关重要。鉴于模型车的计算能力有限以及低延迟实时应用的必要性,该堆栈采用 C++ 实现,使用 YOLO Version 5 s 进行环境感知,并利用最先进的机器人操作系统 (ROS) 进行进程间通信。我们相信,这篇文章和随附的开源软件将成为未来参加自动驾驶学生竞赛团队的宝贵资源。我们的工作可作为新手团队的基础工具和经验丰富的参赛者的参考资料。代码和数据可在 GitHub 上公开获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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