Shielding for Higher-Order Safety
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Abstract (arXiv)
Safety shields are runtime enforcement mechanisms that restrict the actions of a controller to guarantee safety. Classical shields are usually synthesised for state predicates: the current physical state is either safe or unsafe, and the shield disables precisely those actions that can force the system into an unsafe state in the future. In many cyber-physical applications this view is too coarse. A vehicle approaching an obstacle should not only avoid collision, but also respect speed regulations, force limits induced by acceleration, and jerk limits to prevent injuries. From a physical perspective, these requirements are predicated over the derivatives of the state. This paper develops a finite-state safety-game construction for such high-order smoothness constraints. We define differential safety properties using finite differences over a discretised state space, characterise their expressiveness, and reduce shield synthesis to an ordinary safety game over a history state space. We give a synthesis algorithm whose shields store exactly k past states for properties of order k and prove that this memory is necessary. We describe an iterative synthesis procedure for a maximally permissive shield that operates over hierarchies of derivative constraints. The algorithm solves constraints iteratively in increasing order and uses the solution at each iteration to prune the state space for the next constraint. This makes shield synthesis more efficient in practice, as the algorithm refrains from exploring large regions of the state space that are known to be unsafe.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 37 references that are in the map. First posted on arXiv 4 Aug 2026.
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14 of 37 references.
References · 14
- 2017Safe Reinforcement Learning via Shieldingcited by 449
- 2019Control Barrier Functions: Theory and Applicationscited by 372
- 2017A General Safety Framework for Learning-Based Control in Uncertain Robotic Systemscited by 163
- 2018A predictive safety filter for learning-based control of constrained nonlinear dynamical systemscited by 118
- 2023The Safety Filter: A Unified View of Safety-Critical Control in Autonomous Systemscited by 88
- 2022Safe Reinforcement Learning via Shielding under Partial Observabilitycited by 56
- 2015Shield Synthesis: Runtime Enforcement for Reactive Systemscited by 42
- 2015Robust Online Monitoring of Signal Temporal Logiccited by 39
- 2021Jerk-limited Real-time Trajectory Generation with Arbitrary Target Statescited by 16
- 2024Shield Synthesis for LTL Modulo Theoriescited by 12
- 2019Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systemscited by 8
- 2013Looking at Mean-Payoff and Total-Payoff through Windowscited by 3
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