# CARVE：交互驾驶中被否决操作的认证可负担修复

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-05-31 08:00
- AIHOT 分数：45
- AIHOT 链接：https://aihot.virxact.com/items/cmqetakp005fjslunwfjcglhe
- 原文链接：https://arxiv.org/abs/2606.02641

## AI 摘要

CARVE是一个无预测的交互驾驶认证层，基于有限格点上的合作包络B_j(s)=β(π_j)α_j^max(s)，对被否决操作进行修复认证。在589个INTERACTION回放片段中，CARVE-Greedy接受了98.64%的初始否决动作，恢复了370/378个人工假否决，同时保持了589/589路权尊重、零优先级智能体假阳性与400/400负应力否决。CARVE不依赖预测或要求其他驾驶员合规，仅认证提议交互是否有界、可归因且符合规范。

## 正文

Interactive driving exposes a failure mode that is easy to miss in rule-aware autonomous-driving stacks: a hard-rule margin can be negative for an ego candidate even though a small lawful accommodation by a non-priority agent would restore feasibility. Existing rulebooks, shields, and reachability filters are strong at vetoing unsafe actions, while prediction-based planners model likely responses. Neither returns a runtime proof object that states which bounded multi-agent edit repairs the maneuver, who owns the edit, whether the request is right-of-way affordable, and what ego fallback remains if the request is not observed. We formulate this missing object as *interactive repair certification* and introduce *CARVE*, a prediction-free certificate layer over a finite lattice of ego-owned and agent-owned tactical operators. Agent-owned requests are admissible only inside \(B_j(s) = β(π_j)α_j^{\max}(s)\), a cooperation envelope that separates kinematic reachability from normative priority. The resulting certificate records the binding rule, repair category, repair set, responsibility-weighted cost split, and fallback. On 589 Lanelet2-geometry-grounded INTERACTION replay episodes, CARVE-Greedy accepts 98.64% of initially vetoed maneuvers and recovers 370/378 human-resolved false vetoes, while preserving 589/589 right-of-way respect, zero priority-agent false positives, and 400/400 negative-stress vetoes. We prove certificate soundness, structural right-of-way respect, exact finite-lattice minimality, fallback contingency, and blame-consistency conditions. CARVE does not predict or require another driver's compliance; it certifies whether a proposed interaction is bounded, attributable, and normatively admissible under declared assumptions.