{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3FJ6IG5KUGO7XCBWHAZZQSKBO3","short_pith_number":"pith:3FJ6IG5K","canonical_record":{"source":{"id":"2503.02076","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-03T21:57:28Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"a947ff4ee5a184c8dd7a948cbf40a3893124f3075f8299f8f3d145d42ab6e41e","abstract_canon_sha256":"cc4e564ebe2d0c4012e250e2ac91017e69cc6b0e680e3398d82b5629c7accce1"},"schema_version":"1.0"},"canonical_sha256":"d953e41baaa19dfb8836383398494176fef28aeb4d24e3f3cae958367df4d553","source":{"kind":"arxiv","id":"2503.02076","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.02076","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"arxiv_version","alias_value":"2503.02076v1","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.02076","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"pith_short_12","alias_value":"3FJ6IG5KUGO7","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"pith_short_16","alias_value":"3FJ6IG5KUGO7XCBW","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"pith_short_8","alias_value":"3FJ6IG5K","created_at":"2026-07-05T10:23:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3FJ6IG5KUGO7XCBWHAZZQSKBO3","target":"record","payload":{"canonical_record":{"source":{"id":"2503.02076","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-03T21:57:28Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"a947ff4ee5a184c8dd7a948cbf40a3893124f3075f8299f8f3d145d42ab6e41e","abstract_canon_sha256":"cc4e564ebe2d0c4012e250e2ac91017e69cc6b0e680e3398d82b5629c7accce1"},"schema_version":"1.0"},"canonical_sha256":"d953e41baaa19dfb8836383398494176fef28aeb4d24e3f3cae958367df4d553","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:23:36.125970Z","signature_b64":"hQqIp5bJusmeorBDODQaUhgRIKLZDd5+XMA3Vz7FmwmU+veQZw1fRJ1ruX2kjPhxPIf8JJJ+xpOlGPkSW76uAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d953e41baaa19dfb8836383398494176fef28aeb4d24e3f3cae958367df4d553","last_reissued_at":"2026-07-05T10:23:36.125358Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:23:36.125358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.02076","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:23:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tqMOq/awOEXpKg1WJAp2wi96d4r0WkzJFdQxbqEloAj27DJqH53zhOHwMdNwMCvff81Jt4+RgHKEBamm8T6OCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T09:19:45.910238Z"},"content_sha256":"0dae1bbcb187ab9d3a21ed566721886156dbc00612d3063a708bb7c193064157","schema_version":"1.0","event_id":"sha256:0dae1bbcb187ab9d3a21ed566721886156dbc00612d3063a708bb7c193064157"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3FJ6IG5KUGO7XCBWHAZZQSKBO3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CorrA: Leveraging Large Language Models for Dynamic Obstacle Avoidance of Autonomous Vehicles","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Andreas A. Malikopoulos, Panagiotis Typaldos, Shanting Wang","submitted_at":"2025-03-03T21:57:28Z","abstract_excerpt":"In this paper, we present Corridor-Agent (CorrA), a framework that integrates large language models (LLMs) with model predictive control (MPC) to address the challenges of dynamic obstacle avoidance in autonomous vehicles. Our approach leverages LLM reasoning ability to generate appropriate parameters for sigmoid-based boundary functions that define safe corridors around obstacles, effectively reducing the state-space of the controlled vehicle. The proposed framework adjusts these boundaries dynamically based on real-time vehicle data that guarantees collision-free trajectories while also ensu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.02076","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2503.02076/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:23:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DZ9cuC2LuSdu7tJHH4UXiO7cIt13RgMu0WLrhU4Ku/oQGMjgM89mQxxhsK0ssZNdd/9bTo4Bj9L2uSxbukNoBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T09:19:45.910760Z"},"content_sha256":"bb1878bd944bfcd5faf46dd262ea32492434132c69ce1ae73e5d330eccdcfcb8","schema_version":"1.0","event_id":"sha256:bb1878bd944bfcd5faf46dd262ea32492434132c69ce1ae73e5d330eccdcfcb8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3/bundle.json","state_url":"https://pith.science/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T09:19:45Z","links":{"resolver":"https://pith.science/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3","bundle":"https://pith.science/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3/bundle.json","state":"https://pith.science/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3FJ6IG5KUGO7XCBWHAZZQSKBO3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3FJ6IG5KUGO7XCBWHAZZQSKBO3","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"cc4e564ebe2d0c4012e250e2ac91017e69cc6b0e680e3398d82b5629c7accce1","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-03T21:57:28Z","title_canon_sha256":"a947ff4ee5a184c8dd7a948cbf40a3893124f3075f8299f8f3d145d42ab6e41e"},"schema_version":"1.0","source":{"id":"2503.02076","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.02076","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"arxiv_version","alias_value":"2503.02076v1","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.02076","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"pith_short_12","alias_value":"3FJ6IG5KUGO7","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"pith_short_16","alias_value":"3FJ6IG5KUGO7XCBW","created_at":"2026-07-05T10:23:36Z"},{"alias_kind":"pith_short_8","alias_value":"3FJ6IG5K","created_at":"2026-07-05T10:23:36Z"}],"graph_snapshots":[{"event_id":"sha256:bb1878bd944bfcd5faf46dd262ea32492434132c69ce1ae73e5d330eccdcfcb8","target":"graph","created_at":"2026-07-05T10:23:36Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2503.02076/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we present Corridor-Agent (CorrA), a framework that integrates large language models (LLMs) with model predictive control (MPC) to address the challenges of dynamic obstacle avoidance in autonomous vehicles. Our approach leverages LLM reasoning ability to generate appropriate parameters for sigmoid-based boundary functions that define safe corridors around obstacles, effectively reducing the state-space of the controlled vehicle. The proposed framework adjusts these boundaries dynamically based on real-time vehicle data that guarantees collision-free trajectories while also ensu","authors_text":"Andreas A. Malikopoulos, Panagiotis Typaldos, Shanting Wang","cross_cats":["cs.SY","eess.SY"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-03T21:57:28Z","title":"CorrA: Leveraging Large Language Models for Dynamic Obstacle Avoidance of Autonomous Vehicles"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.02076","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0dae1bbcb187ab9d3a21ed566721886156dbc00612d3063a708bb7c193064157","target":"record","created_at":"2026-07-05T10:23:36Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"cc4e564ebe2d0c4012e250e2ac91017e69cc6b0e680e3398d82b5629c7accce1","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-03T21:57:28Z","title_canon_sha256":"a947ff4ee5a184c8dd7a948cbf40a3893124f3075f8299f8f3d145d42ab6e41e"},"schema_version":"1.0","source":{"id":"2503.02076","kind":"arxiv","version":1}},"canonical_sha256":"d953e41baaa19dfb8836383398494176fef28aeb4d24e3f3cae958367df4d553","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d953e41baaa19dfb8836383398494176fef28aeb4d24e3f3cae958367df4d553","first_computed_at":"2026-07-05T10:23:36.125358Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:23:36.125358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hQqIp5bJusmeorBDODQaUhgRIKLZDd5+XMA3Vz7FmwmU+veQZw1fRJ1ruX2kjPhxPIf8JJJ+xpOlGPkSW76uAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:23:36.125970Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.02076","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0dae1bbcb187ab9d3a21ed566721886156dbc00612d3063a708bb7c193064157","sha256:bb1878bd944bfcd5faf46dd262ea32492434132c69ce1ae73e5d330eccdcfcb8"],"state_sha256":"4f4862377d00ef620be947ad67662e7925299425e438ad13f332842b77ca60c6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wo8L1jw7wwDdgS37MjWIwKbA5TZ2z4xrWY77WMjbhN/w+6IqE5CZ3xNad8johnKnHYf1ulnuTWdUDLuyCc4kDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T09:19:45.914425Z","bundle_sha256":"58c7e85a4931f4e4e6537598fe2113455af146d1152f80c426ef70291c00826e"}}