{
  "id": 386,
  "url": "https://arxiv.org/abs/2606.31844v1",
  "title": "Bridging Local Observation and Global Simulation in Closed-Loop Traffic Modeling",
  "summary": "A local-to-global context mismatch arises when autoregressive traffic simulators trained on ego-centric driving logs are deployed in globally observable closed-loop environments. In such logs, the ego vehicle has rich local observations, while surrounding agents are only partially observed due to perception limits and occlusions. As a result, simulators may learn incomplete context--action mappings that remain hidden in log-based training but emerge during closed-loop rollouts, leading to unreal",
  "authors": "Ziyan Wang, Tan Xiang, Peng Chen, Xintao Yan",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-30T15:45:34.000Z",
  "fetched_at": "2026-07-14T14:14:28.439Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/386",
  "original_url": "https://arxiv.org/abs/2606.31844v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}