TUM团队用自主赛车算法突破极限操控，赢下首届阿布扎比自动驾驶赛车联赛。
Head-to-Head autonomous racing at the limits of handling in the A2RL challenge
- 采用仿人类驾驶的控制算法，实现极限性能下的多车协同
- 在阿布扎比赛道上完成高速竞速并夺冠，验证系统鲁棒性
- 适合对自动驾驶、智能赛车感兴趣的工程师与研究者
自主赛车面临车辆在极限性能与动态条件下运行时的多智能体交互挑战，是推动自动驾驶技术发展和提升道路安全的重要研究与测试环境。本文介绍了慕尼黑工业大学（TUM）自动驾驶赛车队为首届阿布扎比自动驾驶赛车联盟（A2RL）开发的算法与部署策略。团队通过软件模拟人类驾驶行为，在极限操控与多车互动中实现优异表现，最终赢得比赛。文章还总结了成功的关键因素，并分享了最重要的实践经验。
原文摘要 · Abstract (English)
Autonomous racing presents a complex challenge involving multi-agent interactions between vehicles operating at the limit of performance and dynamics. As such, it provides a valuable research and testing environment for advancing autonomous driving technology and improving road safety. This article presents the algorithms and deployment strategies developed by the TUM Autonomous Motorsport team for the inaugural Abu Dhabi Autonomous Racing League (A2RL). We showcase how our software emulates human driving behavior, pushing the limits of vehicle handling and multi-vehicle interactions to win the A2RL. Finally, we highlight the key enablers of our success and share our most significant learnings.
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