ミッションパフォーマンス：自動運転レースのための自動適応型レースペース進行
Mission Performance: Automatic and Adaptive Race Pace Progression for Autonomous Racing
完全自動運転レースカーにおいて、安全性を確保しつつラップタイムを短縮するため、セクターごとに車両性能を適応的に調整するモジュールを開発し、実車で有効性を実証した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Giovanni Lambertini, Matteo Pini, Nicola Musiu, Ayoub Raji, Francesco Iacovacci, Marko Bertogna
分類: cs.RO, cs.SE, eess.SY
原文アブストラクト
In this paper, we describe the Mission Performance module implemented for a fully autonomous racing car to automatically manage the longitudinal, lateral, and combined performances, aiming to speedup the laptime progression while assuring safety. Motivated by the difficulty and risks of applying the real-time estimation of the grip to critical modules like the motion planner and controller, the Mission Performance guides these modules adapting their target performance instead of changing the vehicle model parameters. The module is formed by pre-defined progressions to warm up the tires at the beginning of a run. Then, the system continuously monitors safety and vehicle dynamics metrics on a per-sector basis to adaptively reduce, maintain, or increase the performance levels for each sector, progressively converging toward the maximum allowed value. The solution's effectiveness is demonstrated on the EAV-25, a fully autonomous Dallara Superformula, at the Yas Marina Circuit during the Abu Dhabi Autonomous Racing League (A2RL) Season 2.
