This work introduces the concept of collapse anticipation, a new governance mechanism for autonomous and cyber-physical systems. It explains why identity and security models designed for cloud microservices cannot be applied to real-time embodied systems such as self-driving cars, robots, and safety-critical control loops. Microservices operate on discrete requests and can tolerate failure, retry, and revocation. Autonomous systems operate on continuous physical trajectories and cannot be restarted or rolled back without risking catastrophic outcomes. The paper builds on the substrate-rooted identity doctrine, which defines identity as a multi-layer trajectory across substrate, execution, behavior, and attestation. It summarizes the axioms of identity preservation and the identity collapse taxonomy, which describe how identity drifts and how collapse propagates through the system. Using these foundations, the work formalizes identity drift, drift boundaries, and drift propagation in a way that applies directly to real-time systems. Collapse anticipation extends this doctrine by detecting identity drift before it reaches a collapse threshold. It introduces the idea of monitoring drift rate as an early-warning signal for instability in perception, execution, behavior, or attestation. The paper explains how anticipatory intervention mechanisms such as controlled stop, limp-home mode, or constrained behavioral envelopes can preserve system identity when drift accelerates. This approach provides a proactive alternative to reactive identity and access management models. The result is a unified framework for identity-conditioned governance in autonomous systems. It connects identity theory, real-time systems engineering, and safety-critical robotics, offering a principled way to reason about stability, drift, and intervention in systems that cannot rely on microservice-style assumptions. This work is intended for researchers in AI safety, cyber-physical systems, autonomous vehicles, robotics, identity governance, and real-time control.