{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2UR4CMUS7G3E46KS2S6NYYVINE","short_pith_number":"pith:2UR4CMUS","schema_version":"1.0","canonical_sha256":"d523c13292f9b64e7952d4bcdc62a8691016d8dbb4728e44ac02b81df4890b12","source":{"kind":"arxiv","id":"1702.00135","version":2},"attestation_state":"computed","paper":{"title":"Analysis of Unprotected Intersection Left-Turn Conflicts based on Naturalistic Driving Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"David J. LeBlanc, Ding Zhao, Huei Peng, Xinpeng Wang","submitted_at":"2017-02-01T05:12:58Z","abstract_excerpt":"Analyzing and reconstructing driving scenarios is crucial for testing and evaluating automated vehicles. This research analyzed left turn / straight-driving conflicts at unprotected intersections by extracting actual vehicle motion data from a naturalistic driving database collected by the University of Michigan. Nearly 7,000 Left turn across path opposite direction (LTAP/OD) events involving heavy trucks and light vehicles were extracted and used to build a stochastic model of such LTAP/OD scenarios. Statistical analysis showed that vehicle type is a significant factor, whereas the change of "},"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":"1702.00135","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2017-02-01T05:12:58Z","cross_cats_sorted":[],"title_canon_sha256":"def9d64fc3f3a0b5ce15d442c3bb6d0b68bf79b588a48ca9eb4f3d1e58391d19","abstract_canon_sha256":"561df5de4595780a23cf9310a523d046654ae0d1fb40eeb865a1575ad5ab6d30"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:47:26.212891Z","signature_b64":"r53YGdiRvy/YiqClKS12ns22qqsHx3aG/P3FJteXOR7U61fVu4YHTfa79D2l7e2zHmX7DFTQfYoMgmBTW6pbCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d523c13292f9b64e7952d4bcdc62a8691016d8dbb4728e44ac02b81df4890b12","last_reissued_at":"2026-05-18T00:47:26.212150Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:47:26.212150Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Analysis of Unprotected Intersection Left-Turn Conflicts based on Naturalistic Driving Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"David J. LeBlanc, Ding Zhao, Huei Peng, Xinpeng Wang","submitted_at":"2017-02-01T05:12:58Z","abstract_excerpt":"Analyzing and reconstructing driving scenarios is crucial for testing and evaluating automated vehicles. This research analyzed left turn / straight-driving conflicts at unprotected intersections by extracting actual vehicle motion data from a naturalistic driving database collected by the University of Michigan. Nearly 7,000 Left turn across path opposite direction (LTAP/OD) events involving heavy trucks and light vehicles were extracted and used to build a stochastic model of such LTAP/OD scenarios. Statistical analysis showed that vehicle type is a significant factor, whereas the change of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.00135","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1702.00135","created_at":"2026-05-18T00:47:26.212275+00:00"},{"alias_kind":"arxiv_version","alias_value":"1702.00135v2","created_at":"2026-05-18T00:47:26.212275+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.00135","created_at":"2026-05-18T00:47:26.212275+00:00"},{"alias_kind":"pith_short_12","alias_value":"2UR4CMUS7G3E","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2UR4CMUS7G3E46KS","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2UR4CMUS","created_at":"2026-05-18T12:30:55.937587+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/2UR4CMUS7G3E46KS2S6NYYVINE","json":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE.json","graph_json":"https://pith.science/api/pith-number/2UR4CMUS7G3E46KS2S6NYYVINE/graph.json","events_json":"https://pith.science/api/pith-number/2UR4CMUS7G3E46KS2S6NYYVINE/events.json","paper":"https://pith.science/paper/2UR4CMUS"},"agent_actions":{"view_html":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE","download_json":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE.json","view_paper":"https://pith.science/paper/2UR4CMUS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1702.00135&json=true","fetch_graph":"https://pith.science/api/pith-number/2UR4CMUS7G3E46KS2S6NYYVINE/graph.json","fetch_events":"https://pith.science/api/pith-number/2UR4CMUS7G3E46KS2S6NYYVINE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE/action/storage_attestation","attest_author":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE/action/author_attestation","sign_citation":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE/action/citation_signature","submit_replication":"https://pith.science/pith/2UR4CMUS7G3E46KS2S6NYYVINE/action/replication_record"}},"created_at":"2026-05-18T00:47:26.212275+00:00","updated_at":"2026-05-18T00:47:26.212275+00:00"}