mlsanityData to 14 Oct 2026

Verification of Autonomous Neural Car Control with KeYmaera X

arXiv 2504.03272 ↗First posted 4 Apr 2025eess.SY cs.AI cs.LGcited by 1

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Abstract (arXiv)

This article presents a formal model and formal safety proofs for the ABZ'25 case study in differential dynamic logic (dL). The case study considers an autonomous car driving on a highway avoiding collisions with neighbouring cars. Using KeYmaera X's dL implementation, we prove absence of collision on an infinite time horizon which ensures that safety is preserved independently of trip length. The safety guarantees hold for time-varying reaction time and brake force. Our dL model considers the single lane scenario with cars ahead or behind. We demonstrate that dL with its tools is a rigorous foundation for runtime monitoring, shielding, and neural network verification. Doing so sheds light on inconsistencies between the provided specification and simulation environment highway-env of the ABZ'25 study. We attempt to fix these inconsistencies and uncover numerous counterexamples which also indicate issues in the provided reinforcement learning environment.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 9 of its 35 references that are in the map. First posted on arXiv 4 Apr 2025.

Builds on

9 of 35 references.

References · 9

  1. 2024The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Resultscited by 43
  2. 2019Verifiably Safe Off-Model Reinforcement Learningcited by 16
  3. 2022Correct-by-Construction Runtime Enforcement in AI -- A Surveycited by 12
  4. 2024Provably Safe Neural Network Controllers via Differential Dynamic Logiccited by 7
  5. 2023CESAR: Control Envelope Synthesis via Angelic Refinementscited by 5
  6. 2016A Complete Uniform Substitution Calculus for Differential Dynamic Logiccited by 3
  7. 2018Verified Runtime Validation for Partially Observable Hybrid Systemscited by 3
  8. 2024Uniform Substitution for Differential Refinement Logiccited by 2
  9. 2019HyPLC: Hybrid Programmable Logic Controller Program Translation for Verificationcited by 1

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Citing papers per year: 2025: 1.

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  1. 2023Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach
  2. 2026GuardAD: Safeguarding Autonomous Driving MLLMs via Markovian Safety Logic
  3. 2025Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving
  4. 2021Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehicles
  5. 2025Knowledge Integration Strategies in Autonomous Vehicle Prediction and Planning: A Comprehensive Survey
  6. 2024Model Checking for Reinforcement Learning in Autonomous Driving: One Can Do More Than You Think!
  7. 2026Reason--Imagine--Act: Closed-Loop LLM Decision Making with World Models for Autonomous Driving
  8. 2026A Neuro-Symbolic Framework Combining Inductive and Deductive Reasoning for Autonomous Driving Planning