让自动驾驶车在红绿灯路口智能判断是否该省油，避免因感知出错导致失控。
Integrity-Gated Eco-CACC: Epistemic Admissibility for Cooperative Driving at Signalized Intersections
- 通过位置、可观测性与语义一致性构建统一可信度指标
- 当系统可信度下降时自动切换到安全模式，保持效率与安全平衡
- 适合追求高能效又需可靠性的智能驾驶系统研发者
Eco-协同自适应巡航控制（Eco-CACC）系统依赖精准定位、信号灯时序和交互感知来优化红绿灯路口的能耗。现有方法通常假设内部世界模型始终有效，但在传感中断或语义不一致导致规划前提失效时易出错。本文提出一种完整性门控的Eco-CACC框架，显式监控车辆内信念与外部感知的一致性。通过融合位置创新、可观测性损失与语义不一致，构建统一的可信度度量，并据此调节控制权限，实现正常节能驾驶与安全优先退避模式之间的动态切换。不同于鲁棒控制在不确定性下维持性能的做法，本框架决定能量最优控制是否仍可接受。基于场景的仿真表明：当模型一致性保持时，系统维持正常能效；在完整性下降时，能提前且保守响应，保障安全性。
原文摘要 · Abstract (English)
Eco-Cooperative Adaptive Cruise Control (Eco-CACC) systems rely on accurate localization, signal timing, and interaction awareness to optimize energy consumption at signalized intersections. Existing approaches typically assume that the internal world model used for optimization remains valid, making them vulnerable when sensing outages or semantic inconsistencies invalidate planning premises. This letter proposes an Integrity-Gated Eco-CACC framework that explicitly monitors the consistency between internal vehicle beliefs and external sensing. A unified integrity metric is constructed by combining positional innovation, observability loss, and semantic inconsistencies. The resulting trust score regulates control authority, enabling a transition between nominal eco-driving and a safety-dominant fallback maneuver. Unlike robust control methods that attempt to preserve performance under uncertainty, the proposed framework regulates whether energy-optimal control remains admissible. Scenario-based simulations demonstrate that the method preserves nominal efficiency when model consistency is maintained, while enabling early and conservative responses under integrity degradation.
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