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Worst-Case Hidden-Vehicle Trajectory Search in Spatiotemporal Occlusion Regions — arXiv:2609.20480

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.20480
License (as archived): CC0-1.0
Archived: 2026-10-10T04:00:09.716Z
SHA-256 of the archived text: d7ea21af45579c419f5e848d0f6be76d7b90af33be96ada0170d848bb6a4a86e
Stable URL of this page: https://metraipolis.com/documento/dc_e67f628fe99e

How to cite

Worst-Case Hidden-Vehicle Trajectory Search in Spatiotemporal Occlusion Regions — arXiv:2609.20480 — arXiv (en), https://arxiv.org/abs/2609.20480 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_e67f628fe99e (Metraipolis archive dc_e67f628fe99e, sha256 d7ea21af45579c419f5e848d0f6be76d7b90af33be96ada0170d848bb6a4a86e)

BibTeX

@misc{dce67f628fe99e,
  title = {Worst-Case Hidden-Vehicle Trajectory Search in Spatiotemporal Occlusion Regions — arXiv:2609.20480},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.20480},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_e67f628fe99e; sha256 d7ea21af45579c419f5e848d0f6be76d7b90af33be96ada0170d848bb6a4a86e},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.20480. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Occlusion creates fundamental uncertainty in autonomous driving. Existing methods often propagate frame-wise hypotheses or optimize ego behavior against prescribed hidden-agent predictions, leaving the worst history-consistent interaction unexplored. We introduce History-Conditioned Minimax Trajectory Search (HC-MTS), which combines temporal occlusion reasoning with response-aware search. First, HC-MTS constructs finite hidden-state modes, each certified by a backward witness satisfying multi-frame visibility, occupancy, semantic-map support, and class-specific kinematic constraints. It then solves a bilevel minimax problem: an inner finite oracle maximizes the ego driving score over destination attainment and ride comfort, while the outer search selects the legal hidden-vehicle trajectory that minimizes this best-response value. Across eight Waymo Open Motion Dataset scenarios, increasing the visibility-memory horizon from K=1 to K=20 reduces the mean per-scenario vehicle, pedestrian, and total retained hidden-seed counts by 18.12%, 21.67%, and 18.45%, respectively. HC-MTS identifies six avoidable counterexamples, while no legal collision-producing attacker is found in the remaining two scenes within the finite search budget.

Tema degli esploratori: fiducia digitale e crittografia (retro-catalogo arXiv: annunci del 2026-09-18 in cs.CR).
Categorie arXiv: Robotics (cs.RO) ; Cryptography and Security (cs.CR).
Pagina del lavoro: https://arxiv.org/abs/2609.20480 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-10T03:26:20.901Z dalla pagina https://arxiv.org/catchup/cs.CR/2026-09-18?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).