{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:YUGCW7Y6TPURID57AILJP45DNA","short_pith_number":"pith:YUGCW7Y6","schema_version":"1.0","canonical_sha256":"c50c2b7f1e9be9140fbf021697f3a3681e2f2ffa5cfcf8a8f4881cd9b6428e42","source":{"kind":"arxiv","id":"2408.06351","version":1},"attestation_state":"computed","paper":{"title":"A Probabilistic Approach for Queue Length Estimation Using License Plate Recognition Data: Considering Overtaking in Multi-lane Scenarios","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"eess.SP","authors_text":"Chaopeng Tan, Hao Wu, Jiahao Liu, Keshuang Tang, Lyuzhou Luo","submitted_at":"2024-07-24T09:52:33Z","abstract_excerpt":"Multi-section license plate recognition (LPR) data provides input-output information and sampled travel times of the investigated link, serving as an ideal data source for lane-based queue length estimation in recent studies. However, most of these studies assumed the strict FIFO rule or a specific arrival process, thus ignoring the potential impact of overtaking and the variation of traffic flows, especially in multi-lane scenarios. To address this issue, we propose a probabilistic approach to derive the stochastic queue length by constructing a conditional probability model of no-delay arriv"},"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":"2408.06351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2024-07-24T09:52:33Z","cross_cats_sorted":["math.ST","stat.TH"],"title_canon_sha256":"b2e72b46935068bd5cb41258e45bad6a10f62189c51ae100545db802c6764118","abstract_canon_sha256":"0ab0a230c28ea361280e3d61d6834e5eda7807e2b3861579b557bbd1f89576a4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:54:55.843182Z","signature_b64":"oaoAvwcttVjj2sGk3we19Y7BbXPsJGdFQpwZOwokL3hWzzZhSbL+sdYSVfhwzjSi8goisQB8eQ8p94NFGRY1DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c50c2b7f1e9be9140fbf021697f3a3681e2f2ffa5cfcf8a8f4881cd9b6428e42","last_reissued_at":"2026-07-05T08:54:55.842825Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:54:55.842825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Probabilistic Approach for Queue Length Estimation Using License Plate Recognition Data: Considering Overtaking in Multi-lane Scenarios","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"eess.SP","authors_text":"Chaopeng Tan, Hao Wu, Jiahao Liu, Keshuang Tang, Lyuzhou Luo","submitted_at":"2024-07-24T09:52:33Z","abstract_excerpt":"Multi-section license plate recognition (LPR) data provides input-output information and sampled travel times of the investigated link, serving as an ideal data source for lane-based queue length estimation in recent studies. However, most of these studies assumed the strict FIFO rule or a specific arrival process, thus ignoring the potential impact of overtaking and the variation of traffic flows, especially in multi-lane scenarios. To address this issue, we propose a probabilistic approach to derive the stochastic queue length by constructing a conditional probability model of no-delay arriv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.06351","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/2408.06351/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":"2408.06351","created_at":"2026-07-05T08:54:55.842887+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.06351v1","created_at":"2026-07-05T08:54:55.842887+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.06351","created_at":"2026-07-05T08:54:55.842887+00:00"},{"alias_kind":"pith_short_12","alias_value":"YUGCW7Y6TPUR","created_at":"2026-07-05T08:54:55.842887+00:00"},{"alias_kind":"pith_short_16","alias_value":"YUGCW7Y6TPURID57","created_at":"2026-07-05T08:54:55.842887+00:00"},{"alias_kind":"pith_short_8","alias_value":"YUGCW7Y6","created_at":"2026-07-05T08:54:55.842887+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/YUGCW7Y6TPURID57AILJP45DNA","json":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA.json","graph_json":"https://pith.science/api/pith-number/YUGCW7Y6TPURID57AILJP45DNA/graph.json","events_json":"https://pith.science/api/pith-number/YUGCW7Y6TPURID57AILJP45DNA/events.json","paper":"https://pith.science/paper/YUGCW7Y6"},"agent_actions":{"view_html":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA","download_json":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA.json","view_paper":"https://pith.science/paper/YUGCW7Y6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.06351&json=true","fetch_graph":"https://pith.science/api/pith-number/YUGCW7Y6TPURID57AILJP45DNA/graph.json","fetch_events":"https://pith.science/api/pith-number/YUGCW7Y6TPURID57AILJP45DNA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA/action/storage_attestation","attest_author":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA/action/author_attestation","sign_citation":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA/action/citation_signature","submit_replication":"https://pith.science/pith/YUGCW7Y6TPURID57AILJP45DNA/action/replication_record"}},"created_at":"2026-07-05T08:54:55.842887+00:00","updated_at":"2026-07-05T08:54:55.842887+00:00"}