快適すぎる停滞：Bench2Driveの閉ループ評価プロトコルにおける落とし穴
Comfortably Stuck: Evaluation Pitfalls in Bench2Drive's Closed-Loop Protocol
自動運転モデル評価用ベンチマークBench2Driveの快適性指標とナビゲーション信号供給に実装上の問題があることを示し、距離ベースの修正指標を提案した。
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？
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著者: Thomas Schwarzfischer, Emad Aghajanzadeh, Moritz Thoma, Nael Fasfous, Manoj Rohit Vemparala, Pierpaolo Mori, Daniel Mueller-Gritschneder, Ulf Schlichtmann
分類: cs.RO
原文アブストラクト
Closed-loop evaluation is widely regarded as a more faithful way to assess end-to-end (E2E) driving models than open-loop evaluation, and Bench2Drive, built on the CARLA simulator, has become the dominant benchmark for it. We show that its evaluation protocol itself contains pitfalls that can misrepresent the models scored on it. Bench2Drive's comfort metric, adapted from nuPlan, has several implementation errors and a segmentation scheme that rewards standing still, so it mostly measures how long a vehicle stays stationary, correlating with stationary time at r = 0.97 across eight models. We propose a corrected, distance-based metric that cuts that correlation to r = 0.06. Under it, the strong driving-score/comfort tradeoff the original metric reports is no longer detectable once models are compared at matched driving speed, which suggests that comfort trades against how fast a model drives rather than against how well it drives. We also uncover two pitfalls in how the harness supplies navigation signals: the default controller can replace a model's own steering with an angle toward the route target point, and the target point supplied at evaluation time can differ substantially from what a model saw in training. We demonstrate both on UniAD and VAD, where their effects differ sharply, and argue that future closed-loop evaluations should check for them. We will release all fixes as standalone code, so corrected comfort scores can be obtained from logged trajectories without re-running closed-loop simulation.