Proposed Sampling-based Game-Theoretic Planning (SGTP) framework for multi-behavior autonomous racing. SGTP combines GPU-accelerated sampling-based planning with game-theoretic best-response reasoning, using a new game-aware cost to favor competitive interactions and selecting the lowest-cost feasible trajectory.</p>\n","updatedAt":"2026-08-03T09:28:09.462Z","author":{"_id":"672288dd7055eec76d377268","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/672288dd7055eec76d377268/bBQ51VwKZJIkHkNffuEuJ.jpeg","fullname":"Yuan Gao","name":"Yuan-avs","type":"user","isPro":true,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":3,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.8461737036705017},"editors":["Yuan-avs"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/672288dd7055eec76d377268/bBQ51VwKZJIkHkNffuEuJ.jpeg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2607.25388","authors":[{"_id":"6a705ead02c90f968f48a1dc","name":"Zhouheng Li","hidden":false},{"_id":"6a705ead02c90f968f48a1dd","name":"Fangguo Zhao","hidden":false},{"_id":"6a705ead02c90f968f48a1de","name":"Mattia Piccinini","hidden":false},{"_id":"6a705ead02c90f968f48a1df","name":"Baha Zarrouki","hidden":false},{"_id":"6a705ead02c90f968f48a1e0","name":"Yuan Gao","hidden":false},{"_id":"6a705ead02c90f968f48a1e1","name":"Zitong Shan","hidden":false},{"_id":"6a705ead02c90f968f48a1e2","name":"Johannes Betz","hidden":false},{"_id":"6a705ead02c90f968f48a1e3","name":"Chen Lv","hidden":false},{"_id":"6a705ead02c90f968f48a1e4","name":"Lei Xie","hidden":false}],"mediaUrls":["https://cdn-uploads.huggingface.co/production/uploads/672288dd7055eec76d377268/kz9RKXVY8_sGuhZ9umFni.jpeg"],"publishedAt":"2026-07-28T00:00:00.000Z","submittedOnDailyAt":"2026-08-03T00:00:00.000Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","submittedOnDailyBy":{"_id":"672288dd7055eec76d377268","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/672288dd7055eec76d377268/bBQ51VwKZJIkHkNffuEuJ.jpeg","isPro":true,"fullname":"Yuan Gao","user":"Yuan-avs","type":"user","name":"Yuan-avs"},"summary":"Autonomous multi-vehicle racing requires real-time planning of diverse competitive behaviors in intense interactions. Existing planners often struggle to balance strategic diversity and computational efficiency. To address this challenge, we propose Sampling-based Game-Theoretic Planning (SGTP), a real-time framework that combines game-theoretic reasoning with GPU-accelerated sampling of control sequences and dynamics rollouts. Sampled trajectories are ranked using a game-aware cost to capture competitive interactions and generate diverse racing behaviors. Our planner then performs feasibility selection by explicitly enforcing track-boundary and dynamic collision-avoidance constraints, ensuring safe and reliable transitions between racing strategies. Extensive simulations on challenging tracks show that SGTP achieves a 95.24% win rate and a 99.35% task-completion ratio in highly interactive races, with a mean computational time of 0.095 s over multiple iterative solving steps. We also demonstrate the successful application of SGTP in large-scale scenarios with up to 10 agents. We release our code and provide an open-source benchmark of multi-agent autonomous racing algorithms to facilitate future research. Project page: https://sgtp-racing.github.io/.","upvotes":0,"discussionId":"6a705eae02c90f968f48a1e5","projectPage":"https://sgtp-racing.github.io/","githubRepo":"https://github.com/zhouhengli/SGTP-Racer","githubRepoAddedBy":"user","githubStars":3,"organization":{"_id":"6a4f83663e43ae629a202b05","name":"TUM-AVS","fullname":"TUM - Professorship of Autonomous Vehicle Systems","avatar":"https://cdn-avatars.huggingface.co/v1/production/uploads/6723459e7ddd97700c1c1c6a/AJSXS1Qq8ywx4puQ91Fhm.png"}},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[],"acceptLanguages":["en"],"organization":{"_id":"6a4f83663e43ae629a202b05","name":"TUM-AVS","fullname":"TUM - Professorship of Autonomous Vehicle Systems","avatar":"https://cdn-avatars.huggingface.co/v1/production/uploads/6723459e7ddd97700c1c1c6a/AJSXS1Qq8ywx4puQ91Fhm.png"},"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2607/2607.25388.md","query":{}}">

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