Head-to-Head autonomous racing at the limits of handling in the A2RL challenge

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Authors: Simon Hoffmann, Simon Sagmeister, Tobias Betz, Joscha F. Bongard, Sascha Büttner, Dominic Ebner, Daniel Esser, Georg Jank, Sven Goblirsch, A. Langmann, Maximilian Leitenstern, Levent Ögretmen
+8 more Phillip Pitschi, Ann-Kathrin Schwehn, Cornelius Schröder, Marcel Weinmann, Frederik Werner, Boris Lohmann, Johannes Betz, Markus Lienkamp
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Abstract

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.

Fields of Study & Subjects

Autonomous Vehicle Technology and Safety Vehicle Dynamics and Control Systems Reinforcement Learning in Robotics

Publication details

Journal / source
arXiv (Cornell University)
Publication date
9 February 2026
Language
EN
Document type
Preprint