Runtime Enforcement of Hybrid System Properties

• URL: http://arxiv.org/abs/2606.12022v1
• Date: Wed, 10 Jun 2026 12:46:02 GMT
• Title: Runtime Enforcement of Hybrid System Properties
• Abstract summary: We propose a runtime enforcement framework where safety requirements are modeled using Hybrid Automata (HA)<n>The framework combines discrete-event editing with continuous-time monitoring to support enforcement actions such as suppression, delay, and insertion of events at arbitrary time instants.<n>A detailed case study on an Adaptive Cruise Control (ACC) system demonstrates the effectiveness of the proposed approach.
• Score: 0.38709946720835026
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Runtime enforcement has emerged as a promising approach for ensuring the safety of autonomous and cyber-physical systems operating in uncertain and dynamic environments. Unlike traditional runtime verification, runtime enforcement actively intervenes during execution to prevent property violations by modifying unsafe system behaviors. Existing enforcement frameworks primarily focus on untimed or discrete-time specifications and are often limited to delaying or suppressing events, making them inadequate for reactive systems exhibiting complex continuous dynamics. In this paper, we propose a runtime enforcement framework where safety requirements are modeled using Hybrid Automata (HA). The framework combines discrete-event editing with continuous-time monitoring to support enforcement actions such as suppression, delay, and insertion of events at arbitrary time instants. Upon observing environmental inputs, the automaton is initialized, and runtime reachability analysis is used to synthesize safe corrective actions. We formally define the enforcement problem for safety hybrid automata, establish enforceability conditions, and present an online enforcement algorithm for reactive systems. A detailed case study on an Adaptive Cruise Control (ACC) system demonstrates the effectiveness of the proposed approach in maintaining safety properties under unsafe controller behaviors. Experimental results show that the framework introduces minimal computational overhead while ensuring continuous compliance with safety requirements in real time.

Related papers

• Hamilton-Jacobi Reachability for Hybrid Systems: Unified Goal-Driven Control with Safety Guarantees [8.202941588804972]
  We extend classical Hamilton-Jacobi (HJ) reachability analysis, a formal verification method for continuous-time nonlinear systems, to hybrid dynamical systems.<n>Our framework characterizes safe sets for hybrid systems through a generalized value function defined over both discrete and continuous states.<n>We formulate and compute hybrid backward reach-avoid tubes, enabling the simultaneous enforcement of safety and goal-reaching behavior.
  arXiv  Detail & Related papers  (2026-09-15T16:42:23Z)
• HazardAuditor: From Executable Threats to Safer Computer-Use Agents [50.06351661912873]
  Existing guard models target static prompts and responses.<n>Existing safety platforms produce evaluation verdicts rather than the normalized supervision a guard model needs to learn.<n>We introduce HazardAuditor, an execution-grounded framework that closes both gaps.
  arXiv  Detail & Related papers  (2026-09-14T07:09:33Z)
• Position: AI Safety Requires Effective Controllability [7.789894640525689]
  We argue that AI safety requires controllability as a first-class objective.<n>Experiments with OpenClaw-based agents show that current alignment and guardrail mechanisms reduce risk, but often fail to provide persistent, authoritative, and enforceable runtime control.
  arXiv  Detail & Related papers  (2026-05-26T14:53:24Z)
• Connected Dependability Cage: Run-Time Function and Anomaly Monitoring for the Development and Operation of Safe Automated Vehicles [4.255452662944005]
  Connected Dependability Cage enables hierarchical fail-operational behavior in AI-enabled perception systems.<n>System supports graceful degradation, ultimately enabling a transition to a minimal-risk maneuver strategy.
  arXiv  Detail & Related papers  (2026-04-30T11:20:39Z)
• CORA: Conformal Risk-Controlled Agents for Safeguarded Mobile GUI Automation [68.53387633351484]
  We propose CORA (COnformal Risk-controlled GUI Agent), a post-policy, pre-action safeguarding framework that provides statistical guarantees on harmful executed actions.<n> CORA reformulates safety as selective action execution: we train a Guardian model to estimate action-conditional risk for each proposed step.<n>To rigorously evaluate this paradigm, we introduce Phone-Harm, a new benchmark of mobile safety violations with step-level harm labels.
  arXiv  Detail & Related papers  (2026-04-10T09:41:21Z)
• In Perfect Harmony: Orchestrating Causality in Actor-Based Systems [0.0]
  Actor-based systems present significant challenges for runtime verification.<n>ACTORCHESTRA is a runtime verification framework for Erlang that automatically tracks causality across multi-actor interactions.<n>Three case studies demonstrate ACTORCHESTRA's effectiveness in detecting complex behavioral violations in real-world actor systems.
  arXiv  Detail & Related papers  (2026-03-18T16:47:25Z)
• When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents [90.05202259420138]
  Unintended computer-use agents can deviate from expected outcomes even under benign input contexts.<n>We introduce the first conceptual and methodological framework for unintended CUA behaviors.<n>We propose AutoElicit: an agentic framework that iteratively perturbs benign instructions using CUA execution feedback.
  arXiv  Detail & Related papers  (2026-02-09T03:20:11Z)
• On transferring safety certificates across dynamical systems [2.034258001065168]
  Control barrier functions (CBFs) provide a powerful tool for enforcing safety constraints in control systems.<n>But their direct application to complex, high-dimensional dynamics is often challenging.<n>This paper addresses the problem of transferring safety guarantees between dynamical systems with mismatched dynamics.
  arXiv  Detail & Related papers  (2026-02-03T20:20:08Z)
• RoboSafe: Safeguarding Embodied Agents via Executable Safety Logic [56.38397499463889]
  Embodied agents powered by vision-language models (VLMs) are increasingly capable of executing complex real-world tasks.<n>However, they remain vulnerable to hazardous instructions that may trigger unsafe behaviors.<n>We propose RoboSafe, a runtime safeguard for embodied agents through executable predicate-based safety logic.
  arXiv  Detail & Related papers  (2025-12-24T15:01:26Z)
• Event-Chain Analysis for Automated Driving and ADAS Systems: Ensuring Safety and Meeting Regulatory Timing Requirements [0.0]
  This paper presents a structured, White-Box methodology based on Event-Chain Modeling.<n>Unlike Black-Box approaches, Event-Chain Analysis offers transparent insights into the timing behavior of each functional component.<n>Our methodology enables the derivation, modeling, and validation of end-to-end timing constraints.
  arXiv  Detail & Related papers  (2025-11-22T15:22:05Z)
• CARE: Decoding Time Safety Alignment via Rollback and Introspection Intervention [68.95008546581339]
  Existing decoding-time interventions, such as Contrastive Decoding, often force a severe trade-off between safety and response quality.<n>We propose CARE, a novel framework for decoding-time safety alignment that integrates three key components.<n>The framework achieves a superior balance of safety, quality, and efficiency, attaining a low harmful response rate and minimal disruption to the user experience.
  arXiv  Detail & Related papers  (2025-09-01T04:50:02Z)
• Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection [56.66677293607114]
  We propose Code-as-Monitor (CaM) for both open-set reactive and proactive failure detection.<n>To enhance the accuracy and efficiency of monitoring, we introduce constraint elements that abstract constraint-related entities.<n>Experiments show that CaM achieves a 28.7% higher success rate and reduces execution time by 31.8% under severe disturbances.
  arXiv  Detail & Related papers  (2024-12-05T18:58:27Z)
• SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries [94.84458417662407]
  We introduce SAFE-SIM, a controllable closed-loop safety-critical simulation framework. Our approach yields two distinct advantages: 1) generating realistic long-tail safety-critical scenarios that closely reflect real-world conditions, and 2) providing controllable adversarial behavior for more comprehensive and interactive evaluations. We validate our framework empirically using the nuScenes and nuPlan datasets across multiple planners, demonstrating improvements in both realism and controllability.
  arXiv  Detail & Related papers  (2023-12-31T04:14:43Z)
• Recursively Feasible Probabilistic Safe Online Learning with Control Barrier Functions [60.26921219698514]
  We introduce a model-uncertainty-aware reformulation of CBF-based safety-critical controllers. We then present the pointwise feasibility conditions of the resulting safety controller. We use these conditions to devise an event-triggered online data collection strategy.
  arXiv  Detail & Related papers  (2022-08-23T05:02:09Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.