Ensuring Safe Physical AI in Urban Mobility via Hazard-Informed Synthesized Envelopes

As heterogeneous robotic systems deploy across diverse urban zones, maintaining safety amid complex human-robot interactions remains a critical challenge. We present a unified framework that bridges systematic hazard analysis and runtime enforcement using hazard-informed safety envelopes. Rather than treating safety as a static constraint isolated within individual software modules, we introduce a cross-layer safety transformation process spanning symbolic, spatial, and dynamic world models. We show how this representation naturally interfaces with physical AI runtime harnesses to guarantee safe urban mobility.

Source: arXiv:2608.14481v1 - http://arxiv.org/abs/2608.14481v1 PDF: https://arxiv.org/pdf/2608.14481v1 Original Link: http://arxiv.org/abs/2608.14481v1