CAPE: Closed-Loop Adaptive Planning and Execution for Multi-Node Traffic Fault Recovery

Traffic fault recovery aims to restore network performance after a fault. Existing approaches follow a diagnose-then-control pipeline: localize a root cause and control there. This overlooks two properties: the root cause need not be the most effective control location, and a single intervention cannot restore a network whose congestion keeps evolving. We introduce CAPE (Closed Loop Adaptive Planning and Execution), a closed-loop framework that adjusts interventions as traffic evolves. CAPE uses two-stage decision making: a Planner selects control nodes and measures, and an Executor generates safe actions, enabling effective search in a large hybrid action space. For rare control sets, CAPE calibrates a low-dimensional strategy code via paired simulations and distills it into a generator, improving execution without fine-tuning the full Executor. Across five networks and four fault types, CAPE achieves an average Recovery Gain of 89.70%, exceeding the strongest baseline by 9.15 percentage points. Code is available at https://anonymous.4open.science/r/CPAE-2785.