mlsanityData to 7 Oct 2026

Integrity-Gated Eco-CACC: Epistemic Admissibility for Cooperative Driving at Signalized Intersections

arXiv 2607.18565 ↗First posted 20 Jul 2026eess.SY cs.RO cs.SYcited by 0

On the map: End-to-end autonomous driving → Cooperative and V2X driving

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Cooperative and V2X driving, one of 9 directions in End-to-end autonomous driving. Builds on 1 of its 14 references that are in the map. First posted on arXiv 20 Jul 2026.

Builds on

1 of 14 references.

References · 1

  1. 2024Building Trust in AI-Driven Decision Making for Cyber-Physical Systems (CPS): A Comprehensive Reviewcited by 1

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2024OpenConvoy: Universal Platform for Real-World Testing of Cooperative Driving Systems
  2. 2022Eco-driving for Electric Connected Vehicles at Signalized Intersections: A Parameterized Reinforcement Learning approach
  3. 2022Learning Eco-Driving Strategies at Signalized Intersections
  4. 2024IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
  5. 2024Queue-based Eco-Driving at Roundabouts with Reinforcement Learning
  6. 2025Argus: Resilience-Oriented Safety Assurance Framework for End-to-End ADSs
  7. 2026LANTERN: A Closed-Loop Benchmark for VLM-Based Cooperative Driving with Temporally Grounded Warnings
  8. 2024Optimal Controller Realizations against False Data Injections in Cooperative Driving ↗