arXiv cs.LGPaper
Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment
This is a practical engineering paper aimed at closing the gap between learned planning and certifiable safety, which is the actual bottleneck for autonomous driving deployment, not raw model capability. The hybrid pattern, neural proposal plus deterministic verification layer, is a template worth watching for any safety-critical AI application, not just driving. Useful for teams building agentic systems that need hard guardrails around a probabilistic core.