{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:2XIFXZUDPIF5CZJ5TW73BWHDKA","short_pith_number":"pith:2XIFXZUD","schema_version":"1.0","canonical_sha256":"d5d05be6837a0bd1653d9dbfb0d8e3502ac91afde60dbe79181cc85f4d42646a","source":{"kind":"arxiv","id":"2506.03381","version":1},"attestation_state":"computed","paper":{"title":"Automated Traffic Incident Response Plans using Generative Artificial Intelligence: Part 1 -- Building the Incident Response Benchmark","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.SY"],"primary_cat":"eess.SY","authors_text":"Adriana-Simona Mihaita, Artur Grigorev, Jiwon Kim, Khaled Saleh","submitted_at":"2025-06-03T20:40:44Z","abstract_excerpt":"Traffic incidents remain a critical public safety concern worldwide, with Australia recording 1,300 road fatalities in 2024, which is the highest toll in 12 years. Similarly, the United States reports approximately 6 million crashes annually, raising significant challenges in terms of a fast reponse time and operational management. Traditional response protocols rely on human decision-making, which introduces potential inconsistencies and delays during critical moments when every minute impacts both safety outcomes and network performance. To address this issue, we propose a novel Incident Res"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.03381","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2025-06-03T20:40:44Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SY"],"title_canon_sha256":"58e810b5f7ce0849b6047ba5ca18ef12d82d4017a61d87ec69e16f7a6335f89c","abstract_canon_sha256":"54ad6c4513f8ada407033cfd7594542ce268b13e6baa6829cb40ee5966a62ec7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:15:26.573778Z","signature_b64":"XYkQ8usyMsnk+uygBRKkjDEodHrKEDCwFbyKRnnT8d1MMpRoh9RLnK+M6N9dpBz0w1e7cfS1uneqIZMfjFlSBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5d05be6837a0bd1653d9dbfb0d8e3502ac91afde60dbe79181cc85f4d42646a","last_reissued_at":"2026-07-05T11:15:26.573266Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:15:26.573266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automated Traffic Incident Response Plans using Generative Artificial Intelligence: Part 1 -- Building the Incident Response Benchmark","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.SY"],"primary_cat":"eess.SY","authors_text":"Adriana-Simona Mihaita, Artur Grigorev, Jiwon Kim, Khaled Saleh","submitted_at":"2025-06-03T20:40:44Z","abstract_excerpt":"Traffic incidents remain a critical public safety concern worldwide, with Australia recording 1,300 road fatalities in 2024, which is the highest toll in 12 years. Similarly, the United States reports approximately 6 million crashes annually, raising significant challenges in terms of a fast reponse time and operational management. Traditional response protocols rely on human decision-making, which introduces potential inconsistencies and delays during critical moments when every minute impacts both safety outcomes and network performance. To address this issue, we propose a novel Incident Res"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03381","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/2506.03381/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.03381","created_at":"2026-07-05T11:15:26.573336+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.03381v1","created_at":"2026-07-05T11:15:26.573336+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03381","created_at":"2026-07-05T11:15:26.573336+00:00"},{"alias_kind":"pith_short_12","alias_value":"2XIFXZUDPIF5","created_at":"2026-07-05T11:15:26.573336+00:00"},{"alias_kind":"pith_short_16","alias_value":"2XIFXZUDPIF5CZJ5","created_at":"2026-07-05T11:15:26.573336+00:00"},{"alias_kind":"pith_short_8","alias_value":"2XIFXZUD","created_at":"2026-07-05T11:15:26.573336+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA","json":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA.json","graph_json":"https://pith.science/api/pith-number/2XIFXZUDPIF5CZJ5TW73BWHDKA/graph.json","events_json":"https://pith.science/api/pith-number/2XIFXZUDPIF5CZJ5TW73BWHDKA/events.json","paper":"https://pith.science/paper/2XIFXZUD"},"agent_actions":{"view_html":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA","download_json":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA.json","view_paper":"https://pith.science/paper/2XIFXZUD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.03381&json=true","fetch_graph":"https://pith.science/api/pith-number/2XIFXZUDPIF5CZJ5TW73BWHDKA/graph.json","fetch_events":"https://pith.science/api/pith-number/2XIFXZUDPIF5CZJ5TW73BWHDKA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA/action/storage_attestation","attest_author":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA/action/author_attestation","sign_citation":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA/action/citation_signature","submit_replication":"https://pith.science/pith/2XIFXZUDPIF5CZJ5TW73BWHDKA/action/replication_record"}},"created_at":"2026-07-05T11:15:26.573336+00:00","updated_at":"2026-07-05T11:15:26.573336+00:00"}